CN115829209A - Environment-friendly intelligent warehouse environment-friendly quality analysis method and device based on carbon path - Google Patents
Environment-friendly intelligent warehouse environment-friendly quality analysis method and device based on carbon path Download PDFInfo
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Abstract
The invention relates to a data analysis technology, and discloses a green intelligent warehouse environment-friendly quality analysis method and a device based on a carbon path, which comprises the following steps: constructing an index system hierarchical structure, and determining subjective weight and objective weight according to the index system hierarchical structure; constructing a block matrix according to the subjective weight and the objective weight, and calculating a combined weight according to the block matrix; constructing a standard evaluation model according to the integrated environmental protection index data, calculating the centrality of the standard evaluation model according to the combined weight, and constructing an environmental protection quality evaluation model of the green intelligent warehouse according to the centrality and the evaluation score; and evaluating the green intelligent warehouse to be evaluated by using the green intelligent warehouse environmental protection quality evaluation model, generating an evaluation grade of the green intelligent warehouse to be evaluated, and analyzing the environmental protection quality of the green intelligent warehouse by using the evaluation grade. The environmental protection quality analysis accuracy can be improved.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to an environment-friendly intelligent warehouse quality analysis method and device based on a carbon path.
Background
With the advance of energy saving and emission reduction work, the construction of green warehousing needs to be accelerated, the construction of a green logistics park is encouraged, but in order to construct green warehousing with higher quality, a plurality of index data need to be analyzed, so that the evaluation of the environmental protection quality of the green warehousing is carried out.
The existing environmental protection quality analysis of the green intelligent warehouse is mostly based on single index data to analyze the environmental protection quality. In practical application, various index data which can influence evaluation exist in the evaluation of the environment-friendly quality of the warehouse, and only a single index is considered, so that the environment-friendly quality analysis of the warehouse is possibly too single, and the accuracy of the environment-friendly quality analysis of the green intelligent warehouse is lower.
Disclosure of Invention
The invention provides an environment-friendly intelligent warehouse environment-friendly quality analysis method and device based on a carbon path, and mainly aims to solve the problem of low accuracy in environment-friendly quality analysis.
In order to achieve the purpose, the invention provides a green intelligent warehouse environment-friendly quality analysis method based on a carbon path, which comprises the following steps:
s1, obtaining environmental protection index data of a target green intelligent warehouse, constructing an index system hierarchical structure according to the environmental protection index data, and determining subjective weight of the environmental protection index data according to the index system hierarchical structure;
s2, performing data integration on the environmental protection index data to obtain integrated environmental protection index data, and calculating objective weight of the environmental protection index data according to the integrated environmental protection index data by using a preset entropy weight algorithm;
s3, constructing a block matrix according to the subjective weight and the objective weight, and calculating the combined weight of the environmental protection index data according to the block matrix by using a preset combined weighting algorithm;
s4, constructing a standard evaluation model according to the integrated environmental protection index data, calculating the centrality of the standard evaluation model according to the combined weight, and constructing an environment-friendly intelligent warehouse environmental protection quality evaluation model according to the centrality and a preset evaluation score, wherein the step of calculating the centrality of the standard evaluation model according to the combined weight comprises the following steps:
s41, generating a difference information matrix of the environmental protection index data according to the standard evaluation model;
s42, calculating a bulls-eye coefficient according to the difference information matrix;
s43, calculating the centrality of the standard evaluation model according to the bulls-eye coefficient and the combined weight by using the following centrality calculation formula:
wherein the content of the first and second substances,
in order to be the degree of centrality,
is as follows
The combined weight of the sequence of the individual indices,
to be the number of the index sequences,
for the said target coefficient of the target,
is the first under a standard evaluation model
The sequence of the evaluation indexes is determined by the sequence,
is in the first place
In the individual state mode
An evaluation index sequence;
and S5, evaluating the green intelligent warehouse to be evaluated by using the environment-friendly quality evaluation model of the green intelligent warehouse, generating an evaluation grade of the green intelligent warehouse to be evaluated, and analyzing the environment-friendly quality of the green intelligent warehouse by using the evaluation grade.
Optionally, the determining the subjective weight of the environmental protection index data according to the index system hierarchy includes:
generating a judgment matrix of the hierarchical structure of the index system according to a preset index importance degree;
calculating the index average value of each row in the judgment matrix by using a preset priority formula:
wherein, the first and the second end of the pipe are connected with each other,
is the average value of the indexes,
is a first
Go to the first
The matrix value corresponding to the column is,
the matrix column number of the judgment matrix or the matrix row number of the judgment matrix;
and calculating the index weight of each environmental protection index data in the index system hierarchical structure according to the index average value by using the following weight formula:
wherein, the first and the second end of the pipe are connected with each other,
is the first in the index hierarchy
The index weight of the individual environmental index data,
is as follows
The index average of the row;
and determining whether the judgment matrix meets the consistency by using the preset consistency, and when the judgment matrix meets the consistency, taking the index weight as the subjective weight of the environmental protection index data.
Optionally, the calculating the objective weight of the environmental protection index data according to the integrated environmental protection index data by using a preset entropy weight algorithm includes:
acquiring a target item to be evaluated, and generating an evaluation matrix of the environmental protection index data according to the integrated environmental protection index data and the target item to be evaluated;
determining the index proportion of the target item to be evaluated according to the evaluation matrix;
calculating objective weight of the environmental protection index data according to the index proportion by using the entropy weight algorithm as follows:
wherein the content of the first and second substances,
is as follows
The objective weight of the environmental protection index data,
is a pair ofAs a function of the number of the bits,
is as follows
Under the individual environmental index data
The index proportion of each item to be evaluated,
is the number of items to be rated.
Optionally, the determining the index proportion of the target item to be evaluated according to the evaluation matrix includes:
determining a first evaluation value of the target item to be evaluated according to the evaluation matrix by using a preset first evaluation standard, and determining a second evaluation value of the target item to be evaluated according to the evaluation matrix by using a preset second evaluation standard;
selecting the first evaluation value and the second evaluation value according to a preset target evaluation standard to obtain a target evaluation value;
and determining the index proportion of the target item to be evaluated according to the target evaluation value.
Optionally, the constructing a block matrix according to the subjective weight and the objective weight includes:
generating a subjective weight vector according to the subjective weight;
generating an objective weight vector according to the objective weight;
and carrying out vector splicing on the subjective weight vector and the objective weight vector to obtain a block matrix.
Optionally, the calculating, by using a preset combined weighting algorithm, a combined weight of the environmental protection index data according to the blocking matrix includes:
determining an original decision matrix according to the initial score value of the environmental protection index data, calculating a symmetrical non-negative decision matrix of the original decision matrix, and calculating a symmetrical matrix of the block matrix;
determining a combined matrix according to the symmetric nonnegative definite matrix and the symmetric matrix, and calculating the maximum unit characteristic vector of the combined matrix;
calculating the combined weight of the environmental protection index data according to the maximum unit feature vector and the block matrix by using the combined weighting algorithm as follows:
wherein the content of the first and second substances,
for the said combination weights, the combination weights are,
for the purpose of the block matrix,
is the maximum unit feature vector.
Optionally, the constructing a standard evaluation model according to the integrated environmental protection index data includes:
determining a state model to be evaluated according to the integrated environmental protection index data;
determining an evaluation index sequence of the environmental protection index data according to the state model to be evaluated;
and generating the standard evaluation model according to a preset target mode and the evaluation index sequence.
Optionally, the constructing a green intelligent warehouse environment-friendly quality evaluation model according to the centrality and a preset evaluation score includes:
comparing the evaluation value of each environmental protection index with the central degree to obtain a contrast value;
when the contrast value meets a preset centrality threshold value, determining the environmental protection grade of each environmental protection index;
and generating the environment-friendly quality evaluation model of the green intelligent warehouse according to the environment-friendly grade.
Optionally, the evaluating the to-be-evaluated green intelligent warehouse by using the environment-friendly quality evaluation model of the green intelligent warehouse, and generating the evaluation level of the to-be-evaluated green intelligent warehouse includes:
acquiring to-be-evaluated environmental protection index data of the to-be-evaluated green intelligent warehouse;
calculating the to-be-evaluated centrality of the to-be-evaluated environmental protection index data by using the environment-friendly intelligent warehouse environmental protection quality evaluation model;
and determining the evaluation grade of the green intelligent warehouse to be evaluated according to the centrality to be evaluated and the score corresponding to the environmental index data to be evaluated.
In order to solve the above problems, the present invention further provides an environment-friendly intelligent warehouse quality analysis apparatus based on a carbon path, the apparatus comprising:
the subjective weight determination module is used for acquiring environmental protection index data of a target green intelligent warehouse, constructing an index system hierarchical structure according to the environmental protection index data, and determining the subjective weight of the environmental protection index data according to the index system hierarchical structure;
the objective weight determining module is used for carrying out data integration on the environmental protection index data to obtain integrated environmental protection index data, and calculating the objective weight of the environmental protection index data according to the integrated environmental protection index data by utilizing a preset entropy weight algorithm;
the combination weight calculation module is used for constructing a block matrix according to the subjective weight and the objective weight, and calculating the combination weight of the environmental protection index data according to the block matrix by using a preset combination weighting algorithm;
the environment-friendly quality evaluation model building module is used for building a standard evaluation model according to the integrated environment-friendly index data, calculating the centrality of the standard evaluation model according to the combined weight, and building an environment-friendly intelligent warehouse environment-friendly quality evaluation model according to the centrality and a preset evaluation score;
and the environment-friendly quality analysis module is used for evaluating the green intelligent warehouse to be evaluated by utilizing the environment-friendly quality evaluation model of the green intelligent warehouse, generating the evaluation grade of the green intelligent warehouse to be evaluated, and analyzing the environment-friendly quality of the green intelligent warehouse by utilizing the evaluation grade.
According to the embodiment of the invention, an index system structure is constructed according to the environmental protection index data, and then the subjective weight and the objective weight of the environmental protection index data are determined according to the index system structure; determining the combination weight of the environmental protection index data according to the subjective weight and the objective weight, and further determining the index weight more scientifically and objectively; the centrality of the standard evaluation model is calculated according to the combination weight, and then the environment-friendly quality evaluation model of the green intelligent warehouse is constructed according to the centrality and the evaluation score, so that the construction accuracy of the evaluation model can be improved, the environment-friendly quality of other green warehouses can be accurately analyzed, and the increase of accurate environment-friendly quality evaluation in more green intelligent warehouses is facilitated. Therefore, the carbon path-based environment-friendly intelligent warehouse quality analysis method and device provided by the invention can solve the problem of low accuracy in environment-friendly quality analysis.
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Fig. 1 is a schematic flow chart of an environment-friendly quality analysis method for a green intelligent warehouse based on a carbon path according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of calculating objective weights according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of constructing a block matrix according to an embodiment of the present invention;
fig. 4 is a functional block diagram of an environment-friendly intelligent warehouse quality analysis apparatus based on carbon path according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides an environment-friendly intelligent warehouse quality analysis method based on a carbon path. The executing main body of the green intelligent warehouse environmental protection quality analysis method based on the carbon path includes but is not limited to at least one of electronic devices, such as a server, a terminal and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the green intelligent warehouse environmental quality analysis method based on the carbon path may be performed by software or hardware installed in a terminal device or a server device, and the software may be a block chain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Referring to fig. 1, a schematic flow chart of a green intelligent warehouse environmental quality analysis method based on a carbon path according to an embodiment of the present invention is shown. In this embodiment, the green intelligent warehouse environmental quality analysis method based on the carbon path includes:
s1, obtaining environmental protection index data of a target green intelligent warehouse, constructing an index system hierarchical structure according to the environmental protection index data, and determining subjective weight of the environmental protection index data according to the index system hierarchical structure;
in the embodiment of the invention, the environmental protection index data refers to the warehouse layout, the warehouse geographical position, the warehouse construction material resources, the carbon emission amount of the warehouse and the like of the target green intelligent warehouse, wherein the environmental protection index data of the target green intelligent warehouse can be obtained through field investigation or data search of the target green intelligent warehouse.
In detail, the environmental protection quality of the green intelligent warehouse is analyzed, an index system hierarchical structure of the green intelligent warehouse is constructed according to environmental protection index data, therefore, the index system hierarchical structure constructed according to the environmental protection index data has three layers, the first layer comprises basic requirements of the warehouse, site selection and planning of the warehouse area, land and land utilization, energy and energy utilization, water and water resource utilization, material and material resource utilization and environment composition, the second layer comprises site selection and planning of the warehouse area, land and land utilization, energy and energy utilization, water conservation, water resource utilization, material and material resource utilization, indoor and outdoor environment, pollutant control, greening and the like, and the third layer comprises evaluation items of each index.
Specifically, a proper index weighting method is selected for the constructed index system hierarchical structure, the weight of each index is determined, and the environmental protection quality of the green intelligent warehouse is further analyzed.
In the embodiment of the invention, the subjective weight is represented by an Analytic Hierarchy Process (AHP), and the subjective judgment of experts is mainly used as a basic basis, so that the subjective index weight of each environmental index data is determined by constructing a special evaluation method and a mathematical calculation method. The analytic hierarchy process is a system evaluation and analysis method combining qualitative analysis and quantitative calculation. The various complex factors have different importance in solving the problem, and the relationships among the factors are organized and the relative importance of the different types of factors is listed in order.
In an embodiment of the present invention, the determining the subjective weight of the environmental protection index data according to the hierarchical structure of the index system includes:
generating a judgment matrix of the hierarchical structure of the index system according to a preset index importance degree;
calculating the index average value of each row in the judgment matrix by using a preset priority formula:
wherein the content of the first and second substances,
is the average value of the indexes,
is as follows
Go to the first
The matrix value corresponding to the column is,
the matrix column number of the judgment matrix or the matrix row number of the judgment matrix;
and calculating the index weight of each environmental protection index data in the index system hierarchical structure according to the index average value by using the following weight formula:
wherein the content of the first and second substances,
is the first in the index hierarchy
The index weight of the individual environmental index data,
is as follows
The index average of the row;
and determining whether the judgment matrix meets the consistency by using the preset consistency, and when the judgment matrix meets the consistency, taking the index weight as the subjective weight of the environmental protection index data.
In detail, the function of the judgment matrix is to represent the corresponding importance degree grades of the two schemes in the form of the ratio of the two importance degrees between the indexes. And the index importance degree refers to the index comparison importance degree between different indexes, if index u and index v are compared, if the indexes are equally important, the scale is 1; equally important, the scale is 3; clearly important, the scale is 5; strongly important, the scale is 7; absolute importance, scale is 9; between the two, the scale may be any one of 2,4,6, 8. Thus, the importance between different indicators is determined for the importance of the indicator of the first level relative to the overall goal.
Specifically, the weight of the index for the first layer relative to the total targetImportance, if the index C1 is equally important as the index C2, then
If the index C3 is more strongly insignificant than C4, then
If the index C6 is significantly more important than C1, then
If the two indexes are in the middle, filling numbers between 2,4,6 and 8, and so on, comparing the importance of every two indexes, and adding the important values of the indexes to the corresponding row and column numbers to generate a complete judgment matrix.
Further, the consistency is used for checking whether the judgment matrix meets the consistency, and whether the weight of each index is proper is calculated according to the judgment matrix.
In the embodiment of the present invention, the determining whether the judgment matrix satisfies the consistency by using the preset consistency includes:
performing column normalization on the judgment matrix to obtain a normalized judgment matrix;
utilizing the following characteristic vector calculation formula to normalize the characteristic vector of the judgment matrix;
wherein the content of the first and second substances,
is the first of the normalization matrix
The number of feature vectors is determined by the number of feature vectors,
for the normalized matrix of
Go to the first
The sum of the column matrix values is,
is the number of feature vectors;
determining the maximum eigenvalue of the normalization judgment matrix according to the eigenvector;
determining a consistency index of the judgment matrix according to the maximum eigenvalue;
and when the consistency index is smaller than a preset consistency threshold value, the judgment matrix meets the consistency.
Specifically, for a certain index on the previous layer, the weight of the importance order among the indexes related to the layer is calculated according to the judgment matrix, so the characteristic root and the characteristic vector of the judgment matrix are calculated according to the single sequence of the layer, the consistency index is calculated according to the characteristic value, if the consistency index is smaller than the consistency threshold value 0.1, the judgment matrix is considered to meet the consistency requirement, if the consistency index is larger than the consistency threshold value, the value of the judgment matrix needs to be adjusted, the characteristic vector and the characteristic value are repeatedly calculated, and until the judgment matrix meets the consistency requirement, the index weight is used as the subjective weight of the environmental protection index data.
Specifically, for the evaluation of the environmental protection quality of the green intelligent warehouse, the weight which cannot be obtained by simply using the subjective elements cannot be accurately evaluated, uncertain factors and the difference degree between the evaluation indexes and the evaluation are not considered in the weight distribution, and the evaluation result has one-sidedness and subjectivity. Therefore, subjective assignment is carried out on the environmental protection index data, objective assignment is carried out on the environmental protection index data, and the accuracy of environmental protection quality evaluation on the green intelligent warehouse is further improved.
S2, performing data integration on the environmental protection index data to obtain integrated environmental protection index data, and calculating objective weight of the environmental protection index data according to the integrated environmental protection index data by using a preset entropy weight algorithm;
in the embodiment of the invention, the integration of the environmental protection index data refers to determining an evaluation standard for the environmental protection index data, rating and score division are performed on the environmental protection index data through field interview or data, and the environmental protection index data after the determined rating and score division is used as the integration environmental protection index data.
Illustratively, the environmental protection quality of the green intelligent warehouse can be divided into three grades, namely a primary green warehouse, a secondary green warehouse and a tertiary green warehouse according to the environmental protection integration data, wherein the primary green warehouse is the highest grade, the secondary medium grade and the tertiary is the lowest grade, and the scores are set, namely the score of the primary green warehouse is 100-80, the score of the secondary green warehouse is 79-60 and the score of the tertiary green warehouse is below 60.
In the embodiment of the invention, the objective weight is based on an objective weighting method, and is a quantitative analysis method mainly based on mathematical derivation of target quantity information, so that the most accurate evaluation index of a data source can be guaranteed to obtain the most scientific weight, namely the objective weight of the environmental protection index data is calculated by using an entropy weight method.
In an embodiment of the present invention, referring to fig. 2, the calculating the objective weight of the environmental protection index data according to the integrated environmental protection index data by using a preset entropy weight algorithm includes:
s21, acquiring a target item to be evaluated, and generating an evaluation matrix of the environmental protection index data according to the integrated environmental protection index data and the target item to be evaluated;
s22, determining the index proportion of the target item to be evaluated according to the evaluation matrix;
s23, calculating the objective weight of the environmental protection index data according to the index proportion by using the entropy weight algorithm as follows:
wherein the content of the first and second substances,
is as follows
The objective weight of the environmental protection index data,
in the form of a function of a logarithm,
is as follows
Under the individual environmental index data
The index proportion of each item to be evaluated,
is the number of items to be rated.
In detail, if m items to be evaluated and n evaluation indexes exist, an evaluation matrix corresponding to the corresponding evaluation index of the item to be evaluated is formed and expressed as
And carrying out standardization processing on the evaluation matrix, and determining the index proportion of each target item to be evaluated, so as to determine the objective weight of the environment-friendly index data according to the index proportion.
Specifically, the determining the index proportion of the target item to be evaluated according to the evaluation matrix includes:
determining a first evaluation value of the target item to be evaluated according to the evaluation matrix by using a preset first evaluation standard, and determining a second evaluation value of the target item to be evaluated according to the evaluation matrix by using a preset second evaluation standard;
selecting the first evaluation value and the second evaluation value according to a preset target evaluation standard to obtain a target evaluation value;
and determining the index proportion of the target item to be evaluated according to the target evaluation value.
In detail, the first evaluation criterion is an environmental protection index that is better for a larger evaluation value, and the second evaluation criterion is an environmental protection index that is better for a smaller evaluation value. Therefore, for the first evaluation standard, calculating the maximum value and the minimum value in the evaluation matrix, and comparing the subtraction of the matrix value and the minimum value in the evaluation matrix with the difference between the maximum value and the minimum value to obtain the first evaluation value; and comparing the difference value of the maximum value and the matrix value in the evaluation matrix with the difference value of the maximum value and the minimum value to obtain a second evaluation value according to the second evaluation standard.
Specifically, the first evaluation value and the second evaluation value are selected according to an evaluation criterion of actual environmental protection index data, that is, whether the evaluation criterion of the environmental protection index data is the better the evaluation value is larger or the better the evaluation value is smaller, and when the evaluation value of the environmental protection index data is the better the evaluation value is larger, the first evaluation value is selected; and when the environmental index data is smaller and better in evaluation value, selecting a second evaluation value to obtain a final target evaluation value. And further calculating the index proportion of the target item to be evaluated according to the target evaluation value
I.e. first
Under the individual environmental index data
Index proportion of each item to be evaluated, wherein
，
Is the first
Under the individual environmental index data
Target evaluation values of the individual items to be evaluated.
Further, the objectivity of the subjective weight obtained by independent calculation is too poor, the objective weight obtained by independent calculation may not be consistent with the actual importance of production and life, and in order to determine the index weight more scientifically and objectively, the subjective weight and the objective weight are combined to obtain more accurate index weight.
S3, constructing a block matrix according to the subjective weight and the objective weight, and calculating the combined weight of the environmental protection index data according to the block matrix by using a preset combined weighting algorithm;
in the embodiment of the invention, in order to reflect the influence factors of the subjective and objective index weight, the subjective weight obtained by a chromatographic analysis method is utilized, the objective weight obtained by an entropy weight algorithm is combined to recheck the subjective and objective index weight, and finally, the combined weight of each index data at the bottom layer relative to the top layer is obtained by calculation.
In the embodiment of the invention, the block matrix is a matrix combining subjective weight and objective weight, so that the combined weight of the environmental protection index data is determined according to the block matrix.
In the embodiment of the present invention, referring to fig. 3, the constructing a block matrix according to the subjective weight and the objective weight includes:
s31, generating a subjective weight vector according to the subjective weight;
s32, generating an objective weight vector according to the objective weight;
and S33, carrying out vector splicing on the subjective weight vector and the objective weight vector to obtain a block matrix.
In detail, a subjective weight vector is generated according to the subjective weight corresponding to each environmental protection index data, namely
And generating an objective weight vector according to the objective weight corresponding to each environmental protection index data, namely
So as to splice the subjective weight vector and the objective weight vector to obtain a block matrix
。
Specifically, the optimal weight of the environmental protection index data can be determined according to the block matrix, and then an environmental protection quality model of the green intelligent warehouse is constructed according to the optimal weight, so that the environmental protection quality of the green intelligent warehouse is evaluated, and the accuracy of evaluation can be improved.
In the embodiment of the invention, in order to make the environmental protection quality evaluation values of the green intelligent warehouse have obvious difference, the evaluation values of the environmental protection index data have dispersity as much as possible, namely, the combination weight of the environmental protection index data is calculated by using the sum of squared deviations criterion. Wherein the combinatorial weighting algorithm is an algorithm based on the sum of squared deviations criterion, which is the sum of the squares of the differences between the terms and the mean term.
In an embodiment of the present invention, the calculating, by using a preset combination weighting algorithm, the combination weight of the environmental protection index data according to the blocking matrix includes:
determining an original decision matrix according to the initial score value of the environmental protection index data, calculating a symmetrical non-negative decision matrix of the original decision matrix, and calculating a symmetrical matrix of the block matrix;
determining a combined matrix according to the symmetric nonnegative definite matrix and the symmetric matrix, and calculating the maximum unit characteristic vector of the combined matrix;
calculating the combined weight of the environmental protection index data according to the maximum unit feature vector and the block matrix by using the combined weighting algorithm as follows:
wherein the content of the first and second substances,
for the said combination weights, the combination weights are,
for the purpose of the block matrix,
is the maximum unit feature vector.
In detail, the raw decision matrix
Is based on environmental protectionThe score value initially determined by the index data is constructed, and an original decision matrix is calculated
Symmetric non-negative definite matrix of
And calculating a blocking matrix
Of the symmetric matrix
According to a symmetric matrix
And symmetric non-negative definite matrix
Computing a combinatorial matrix, i.e.
And calculating a combined matrix
The unit feature vector corresponding to the maximum feature root
And finally, calculating the combined weight of the environmental protection index data according to a combined weighting algorithm.
Specifically, after the combination weight of the environmental protection index data is determined, the environmental protection quality evaluation model of the green intelligent warehouse can be constructed by using the combination weight, so that the environmental protection quality evaluation model can be used for comprehensively evaluating the environmental protection quality of a subsequent green intelligent warehouse, and further environmental protection improvement is made according to the comprehensive evaluation.
S4, constructing a standard evaluation model according to the integrated environmental protection index data, calculating the centrality of the standard evaluation model according to the combined weight, and constructing an environment-friendly intelligent warehouse environmental quality evaluation model according to the centrality and a preset evaluation score;
in the embodiment of the invention, in order to more effectively realize the fusion of qualitative analysis and quantitative analysis, realize the condition that both qualitative indexes and quantitative analysis indexes exist in indexes, and be suitable for the condition that the index condition is complex, a standard evaluation model needs to be constructed. The standard evaluation model is based on a gray target model, the gray target model is derived from a gray system theory, namely a standard mode, namely a target center, is determined according to the polarity of each index, each mode and the standard mode are combined to form a gray target, the mode to be evaluated is compared with the standard mode, the degree of the mode to be evaluated approaching the target center, namely the target center degree, is identified, and the mode is identified, graded and optimized based on the target center degree to determine the evaluation grade. Therefore, the qualitative analysis and the quantitative analysis can be fused, and the accuracy of the construction of the evaluation model is improved.
In an embodiment of the present invention, the constructing a standard evaluation model according to the integrated environmental protection index data includes:
determining a state model to be evaluated according to the integrated environmental protection index data;
determining an evaluation index sequence of the environmental protection index data according to the state model to be evaluated;
and generating the standard evaluation model according to a preset target mode and the evaluation index sequence.
In detail, if order
Is the first to be evaluated
The mode of the one state is that,
for green intelligent warehouse environmental protection quality evaluation
A sequence of indicators, then state
Is at the same time
The first under each evaluation index
A mode of an individual state to be evaluated; and
is at the same time
In the individual state mode
And (4) evaluation index sequences. For environment-friendly quality evaluation of the green intelligent warehouse, the standard mode of the positive indexes is the maximum value of the indexes, the standard mode of the negative indexes is the minimum value of the indexes, the positive indexes or the negative indexes are selected according to the required target mode, and then the standard mode sequence is finally determined to be
。
Specifically, in order to improve the accuracy of the evaluation result, the combination weight is introduced into the centrality solution, so that the objectivity can be increased, and the method is more practical.
In an embodiment of the present invention, the calculating the centrality of the standard evaluation model according to the combining weight includes:
generating a difference information matrix of the environmental protection index data according to the standard evaluation model;
calculating a bulls-eye coefficient according to the difference information matrix;
calculating the centrality of the standard evaluation model according to the bulls-eye coefficient and the combined weight by using the following centrality calculation formula:
wherein the content of the first and second substances,
in order to be the degree of centrality,
is as follows
The combined weight of the sequence of the individual indices,
to be the number of the index sequences,
for the said target coefficient of the target,
is the first under the standard evaluation model
The sequence of the evaluation indexes is determined by the sequence,
is in the first place
In the individual state mode
And (4) evaluating index sequences.
In detail, the difference information matrix refers to the difference between different index data in the environmental index data, that is, the difference information matrix is
And calculating the target center coefficient according to the difference information matrix, and determining the target center coefficient according to the maximum value and the minimum value in the difference information matrix.
Specifically, the centrality obtained through calculation can be more practical by using the combination weight in the centrality calculation formula, the accuracy of the evaluation result is improved, and the objectivity is increased. Therefore, the centrality of the central evaluation model, i.e. the bulls-eye degree, is calculated according to the bulls-eye coefficient and the combination weight.
Furthermore, grade evaluation is carried out by comparing the closeness degree of each environmental protection index and the target degree and taking the target degree as a grade division standard, so that an environment-friendly intelligent warehouse environmental quality evaluation model is constructed.
In the embodiment of the invention, the constructing of the environment-friendly intelligent warehouse quality evaluation model according to the centrality and the preset evaluation score comprises the following steps:
comparing the evaluation value of each environmental protection index with the central degree to obtain a contrast value;
when the contrast value meets a preset centrality threshold value, determining the environmental protection grade of each environmental protection index;
and generating the environment-friendly quality evaluation model of the green intelligent warehouse according to the environment-friendly grade.
In detail, the evaluation score of each environmental protection index is compared with the central degree to obtain the closeness of each environmental protection index and the central degree, namely the comparison value is closer to the target center, the higher the grade is, and the farther away from the target center, the lower the grade is.
Specifically, an environment-friendly quality evaluation model of the green intelligent warehouse can be generated according to the environment-friendly grade, and the environment-friendly quality evaluation model of the green intelligent warehouse is used for evaluating the green intelligent warehouse to be evaluated so as to determine the environment-friendly quality of the green intelligent warehouse to be evaluated for evaluation.
And S5, evaluating the green intelligent warehouse to be evaluated by using the green intelligent warehouse environment-friendly quality evaluation model, generating an evaluation grade of the green intelligent warehouse to be evaluated, and analyzing the environment-friendly quality of the green intelligent warehouse by using the evaluation grade.
In the embodiment of the invention, the green intelligent warehouse to be evaluated can be evaluated by directly utilizing the green intelligent warehouse environment-friendly quality evaluation model, the evaluation level of the green intelligent warehouse to be evaluated is determined, and the environment-friendly quality of the green intelligent warehouse is further determined according to the evaluation level.
In the embodiment of the present invention, the evaluating the to-be-evaluated green intelligent warehouse by using the green intelligent warehouse environmental protection quality evaluation model to generate the evaluation level of the to-be-evaluated green intelligent warehouse includes:
acquiring to-be-evaluated environmental protection index data of the to-be-evaluated green intelligent warehouse;
calculating the to-be-evaluated centrality of the to-be-evaluated environmental protection index data by using the environment-friendly intelligent warehouse environmental protection quality evaluation model;
and determining the evaluation grade of the green intelligent warehouse to be evaluated according to the centrality to be evaluated and the score corresponding to the environmental index data to be evaluated.
In detail, an environment-friendly index system structure is constructed according to environment-friendly index data to be evaluated of the environment-friendly intelligent warehouse to be evaluated, combination weight is calculated according to the environment-friendly index system structure, the centrality of the environment-friendly intelligent warehouse to be evaluated is determined according to the combination weight by using an environment-friendly quality evaluation model of the environment-friendly intelligent warehouse to be evaluated, comparison is carried out according to the centrality and a grading score corresponding to the environment-friendly index data to be evaluated, and the evaluation grade of the environment-friendly intelligent warehouse to be evaluated is determined according to the closeness of the centrality and the grading score corresponding to the environment-friendly index data to be evaluated.
Specifically, the environmental quality of the green intelligent warehouse is higher as the evaluation grade is higher, and conversely, the environmental quality of the green intelligent warehouse is lower as the evaluation grade is lower, so that the environmental quality of the green intelligent warehouse can be determined according to the evaluation grade for evaluation, and the environmental deficiency of the green intelligent warehouse in terms of environmental protection can be improved according to the evaluation grade.
According to the embodiment of the invention, an index system structure is constructed according to the environmental protection index data, and then the subjective weight and the objective weight of the environmental protection index data are determined according to the index system structure; determining the combination weight of the environmental protection index data according to the subjective weight and the objective weight, and further determining the index weight more scientifically and objectively; the centrality of the standard evaluation model is calculated according to the combination weight, and then the environment-friendly quality evaluation model of the green intelligent warehouse is constructed according to the centrality and the evaluation score, so that the construction accuracy of the evaluation model can be improved, the environment-friendly quality of other green warehouses can be accurately analyzed, and the increase of accurate environment-friendly quality evaluation in more green intelligent warehouses is facilitated. Therefore, the carbon path-based environment-friendly intelligent warehouse environment-friendly quality analysis method and device provided by the invention can solve the problem of low accuracy in environment-friendly quality analysis.
Fig. 4 is a functional block diagram of an environment-friendly quality analysis apparatus for a green intelligent warehouse based on a carbon path according to an embodiment of the present invention.
The carbon path-based green intelligent warehouse environmental quality analysis apparatus 100 of the present invention may be installed in an electronic device. According to the realized functions, the carbon path-based green intelligent warehouse environmental protection quality analysis device 100 may include a subjective weight determination module 101, an objective weight determination module 102, a combined weight calculation module 103, an environmental protection quality evaluation model construction module 104, and an environmental protection quality analysis module 105. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the subjective weight determination module 101 is configured to obtain environmental protection index data of a target green intelligent warehouse, construct an index system hierarchy according to the environmental protection index data, and determine a subjective weight of the environmental protection index data according to the index system hierarchy;
the objective weight determining module 102 is configured to perform data integration on the environmental protection index data to obtain integrated environmental protection index data, and calculate an objective weight of the environmental protection index data according to the integrated environmental protection index data by using a preset entropy weight algorithm;
the combination weight calculation module 103 is configured to construct a block matrix according to the subjective weight and the objective weight, and calculate a combination weight of the environmental protection index data according to the block matrix by using a preset combination weighting algorithm;
the environment-friendly quality evaluation model building module 104 is configured to build a standard evaluation model according to the integrated environment-friendly index data, calculate a centrality of the standard evaluation model according to the combination weight, and build an environment-friendly intelligent warehouse environment-friendly quality evaluation model according to the centrality and a preset evaluation score;
the environmental protection quality analysis module 105 is configured to evaluate the to-be-evaluated green intelligent warehouse by using the green intelligent warehouse environmental protection quality evaluation model, generate an evaluation level of the to-be-evaluated green intelligent warehouse, and analyze the environmental protection quality of the green intelligent warehouse by using the evaluation level.
In detail, when the modules in the carbon path-based environment-friendly intelligent warehouse quality analysis apparatus 100 according to the embodiment of the present invention are used, the same technical means as the carbon path-based environment-friendly intelligent warehouse quality analysis method described in fig. 1 to 3 are adopted, and the same technical effects can be produced, which is not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the present specification may also be implemented by one unit or means through software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A green intelligent warehouse environmental quality analysis method based on a carbon path is characterized by comprising the following steps:
s1, obtaining environmental protection index data of a target green intelligent warehouse, constructing an index system hierarchical structure according to the environmental protection index data, and determining subjective weight of the environmental protection index data according to the index system hierarchical structure;
s2, performing data integration on the environmental protection index data to obtain integrated environmental protection index data, and calculating objective weight of the environmental protection index data according to the integrated environmental protection index data by using a preset entropy weight algorithm;
s3, constructing a block matrix according to the subjective weight and the objective weight, and calculating the combined weight of the environmental protection index data according to the block matrix by using a preset combined weighting algorithm;
s4, constructing a standard evaluation model according to the integrated environmental protection index data, calculating the centrality of the standard evaluation model according to the combined weight, and constructing an environment-friendly intelligent warehouse environmental protection quality evaluation model according to the centrality and a preset evaluation score, wherein the step of calculating the centrality of the standard evaluation model according to the combined weight comprises the following steps:
s41, generating a difference information matrix of the environmental protection index data according to the standard evaluation model;
s42, calculating a bulls-eye coefficient according to the difference information matrix;
s43, calculating the centrality of the standard evaluation model according to the bulls-eye coefficient and the combined weight by using a following centrality calculation formula:
wherein the content of the first and second substances,
in order to be the degree of centrality,
is as follows
The combined weight of the sequence of the individual indices,
to be the number of the index sequences,
for the said target coefficient of the target,
is the first under the standard evaluation model
The sequence of the evaluation indexes is determined by the sequence,
is in the first place
In the individual state mode
An evaluation index sequence;
s5, evaluating the green intelligent warehouse to be evaluated by using the environment-friendly quality evaluation model of the green intelligent warehouse to generate an evaluation grade of the green intelligent warehouse to be evaluated; and analyzing the environmental protection quality of the green intelligent warehouse by using the evaluation grade.
2. The carbon path-based green intelligent warehouse environmental quality analysis method according to claim 1, wherein the determining the subjective weight of the environmental index data according to the index architecture hierarchy comprises:
generating a judgment matrix of the hierarchical structure of the index system according to a preset index importance degree;
calculating the index average value of each row in the judgment matrix by using a preset priority formula:
wherein the content of the first and second substances,
is the average value of the indexes,
is as follows
Go to the first
The matrix value corresponding to the column is,
the matrix column number of the judgment matrix or the matrix row number of the judgment matrix;
and calculating the index weight of each environmental protection index data in the index system hierarchical structure according to the index average value by using the following weight formula:
wherein the content of the first and second substances,
is the first in the index hierarchy
The index weight of the individual environmental index data,
is as follows
The index average of the row;
and determining whether the judgment matrix meets consistency or not by using preset consistency, and when the judgment matrix meets the consistency, taking the index weight as the subjective weight of the environmental protection index data.
3. The carbon path-based green intelligent warehouse environmental quality analysis method according to claim 1, wherein the calculating the objective weight of the environmental protection index data according to the integrated environmental protection index data by using a preset entropy weight algorithm comprises:
acquiring a target item to be evaluated, and generating an evaluation matrix of the environmental protection index data according to the integrated environmental protection index data and the target item to be evaluated;
determining the index proportion of the target item to be evaluated according to the evaluation matrix;
calculating objective weight of the environmental protection index data according to the index proportion by using the entropy weight algorithm as follows:
wherein the content of the first and second substances,
is as follows
The objective weight of the environmental protection index data,
in the form of a logarithmic function of the function,
is as follows
Under the individual environmental index data
The index proportion of each item to be evaluated,
is the number of items to be rated.
4. The carbon path-based green intelligent warehouse environment-friendly quality analysis method as claimed in claim 3, wherein the determining the index proportion of the target item to be evaluated according to the evaluation matrix comprises:
determining a first evaluation value of the target item to be evaluated according to the evaluation matrix by using a preset first evaluation standard, and determining a second evaluation value of the target item to be evaluated according to the evaluation matrix by using a preset second evaluation standard;
selecting the first evaluation value and the second evaluation value according to a preset target evaluation standard to obtain a target evaluation value;
and determining the index proportion of the target item to be evaluated according to the target evaluation value.
5. The carbon path-based green intelligent warehouse environmental quality analysis method of claim 1, wherein the constructing a blocking matrix according to the subjective weights and the objective weights comprises:
generating a subjective weight vector according to the subjective weight;
generating an objective weight vector according to the objective weight;
and carrying out vector splicing on the subjective weight vector and the objective weight vector to obtain a block matrix.
6. The carbon path-based green intelligent warehouse environmental quality analysis method according to any one of claims 1 to 5, wherein the calculating the combined weight of the environmental index data according to the block matrix by using a preset combined weighting algorithm comprises:
determining an original decision matrix according to the initial score value of the environmental protection index data, calculating a symmetrical non-negative decision matrix of the original decision matrix, and calculating a symmetrical matrix of the block matrix;
determining a combined matrix according to the symmetric nonnegative definite matrix and the symmetric matrix, and calculating the maximum unit characteristic vector of the combined matrix;
calculating the combined weight of the environmental protection index data according to the maximum unit feature vector and the block matrix by using the combined weighting algorithm as follows:
wherein the content of the first and second substances,
for the said combination weights, the combination weights are,
for the purpose of the block matrix,
is the maximum unit feature vector.
7. The carbon path-based green intelligent warehouse environmental quality analysis method according to claim 1, wherein the building of a standard evaluation model according to the integrated environmental index data comprises:
determining a state model to be evaluated according to the integrated environmental protection index data;
determining an evaluation index sequence of the environmental protection index data according to the state model to be evaluated;
and generating the standard evaluation model according to a preset target mode and the evaluation index sequence.
8. The carbon path-based green intelligent warehouse environmental quality analysis method according to claim 1, wherein the building of a green intelligent warehouse environmental quality evaluation model according to the centrality and a preset evaluation score comprises:
comparing the evaluation value of each environmental protection index with the central degree to obtain a contrast value;
when the contrast value meets a preset centrality threshold value, determining the environmental protection grade of each environmental protection index;
and generating the environment-friendly quality evaluation model of the green intelligent warehouse according to the environment-friendly grade.
9. The carbon path-based green intelligent warehouse environmental quality analysis method according to claim 1, wherein the evaluating a green intelligent warehouse to be evaluated by using the green intelligent warehouse environmental quality evaluation model to generate an evaluation grade of the green intelligent warehouse to be evaluated comprises:
acquiring to-be-evaluated environmental protection index data of the to-be-evaluated green intelligent warehouse;
calculating the to-be-evaluated centrality of the to-be-evaluated environmental protection index data by using the environment-friendly intelligent warehouse environmental protection quality evaluation model;
and determining the evaluation grade of the green intelligent warehouse to be evaluated according to the centrality to be evaluated and the score corresponding to the environmental index data to be evaluated.
10. An environment-friendly intelligent warehouse quality analysis device based on a carbon path, which is characterized by comprising:
the subjective weight determination module is used for acquiring environmental protection index data of a target green intelligent warehouse, constructing an index system hierarchical structure according to the environmental protection index data, and determining the subjective weight of the environmental protection index data according to the index system hierarchical structure;
the objective weight determining module is used for carrying out data integration on the environmental protection index data to obtain integrated environmental protection index data, and calculating the objective weight of the environmental protection index data according to the integrated environmental protection index data by utilizing a preset entropy weight algorithm;
the combination weight calculation module is used for constructing a block matrix according to the subjective weight and the objective weight, and calculating the combination weight of the environmental protection index data according to the block matrix by using a preset combination weighting algorithm;
the environment-friendly quality evaluation model building module is used for building a standard evaluation model according to the integrated environment-friendly index data, calculating the centrality of the standard evaluation model according to the combined weight, and building an environment-friendly intelligent warehouse environment-friendly quality evaluation model according to the centrality and a preset evaluation score;
and the environment-friendly quality analysis module is used for evaluating the green intelligent warehouse to be evaluated by utilizing the environment-friendly quality evaluation model of the green intelligent warehouse, generating the evaluation grade of the green intelligent warehouse to be evaluated, and analyzing the environment-friendly quality of the green intelligent warehouse by utilizing the evaluation grade.
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