CN112365123A - Risk analysis method and device in low-water footprint product authentication process - Google Patents
Risk analysis method and device in low-water footprint product authentication process Download PDFInfo
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Abstract
A risk analysis method in the authentication process of a low-water footprint product determines each risk analysis index according to the authentication node and the analysis dimension of the authentication process of the low-water footprint product, establishes a risk analysis model, obtains the trained risk analysis model, realizes the determination of risk information in the authentication process of the low-water footprint product of a sample to be tested, can solve the problems that risk elements are difficult to identify and the authentication risk is difficult to evaluate in the authentication of the low-water footprint product, takes a large amount of data as the training sample, can realize the evaluation and control of the risk in the whole authentication process of the low-water footprint product, and has higher scientificity, effectiveness and practicability.
Description
Technical Field
The invention relates to the field of water resources, in particular to a risk analysis method and device in a low-water-footprint product authentication process.
Background
Water resources are important basic natural resources in human society, and the position of the water resources in the development of the economic society is important. Water footprint (water fountain) refers to the invisible consumption of water by the public during the consumption of products and services in daily life. The water consumed by the product during its production is the water footprint of the product. For example, a 100 gram apple has a "water footprint" of 70 liters, a cup of coffee has a "water footprint" of 140 liters, and a hamburger has a "water footprint" of 2400 liters. The water footprint is an important means for solving the problem of water resource environment, and the water footprint is also used as a new water resource management evaluation tool.
For example, chinese patent document CN111126792A discloses a method for evaluating vulnerability of a regional entity-virtual water resource network, which reveals the degree of dependence of a region on an entity and a virtual water resource and the water supply risk caused by the dependence by the region on the entity and the virtual water resource by quantifying the vulnerability of the regional entity-virtual water resource, thereby providing technical guidance for planning regional entity water and virtual water, reducing the risk inside and outside the water resource network, and relieving the regional water pressure.
Low water footprint products refer to products that consume less water in the production process, and low water footprint product certification refers to certification of products that consume less water in the production process. Low water footprint product certification is a key link in applying this theoretical tool to practice. The implementation of low water footprint product authentication has great significance for fully, reasonably and efficiently utilizing limited water resources and realizing sustainable development of social economy.
Low water footprint product certification risk management and control is an important guarantee to prevent the certification product from being distrusted. Although low-water footprint authentication work is already carried out in part of industries, due to the fact that risk information in the authentication process is not well known by an authentication organization, a risk control system is incomplete, and information collection of an authentication process is not comprehensive, risks in the authentication process have high ambiguity and uncertainty. The certification decision made by the certification authority under the uncertain condition and the supervision of the certification authority after the certification are finished can reduce the credibility of the certification mark of the water footprint product, and even wrong certification judgment can occur.
In chinese patent document CN110909484A, a watershed grey water footprint evaluation method and a water environment management strategy formulation method are disclosed, which are implemented by dividing evaluation units of a watershed to be evaluated according to basic data of the watershed, performing accounting analysis on various pollution positions and river-entering pollution load processes in each evaluation unit to obtain load discharge of various staining elements and the like, measuring and calculating various grey water footprints of the evaluation units, and effectively representing water environment influence of hourly space-scale pollution load drainage.
A method of treating a low water footprint is disclosed in TW201821499A, US20180179568A, which achieves the goal of a low water footprint for the process by reducing the amount of process water through the addition of small amounts of mineral acids and the like.
However, in the prior art, a technical scheme for analyzing risks of a low-water footprint product in an authentication process does not exist, and a problem to be solved is urgently needed.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to provide a method and a device for risk analysis in the authentication process of low-water footprint products by determining the risk of the low-water footprint products in the authentication process.
The embodiment of the invention provides a risk analysis method in a low-water footprint product authentication process, which comprises the following steps:
obtaining an authentication process of the low-water footprint product;
determining each risk analysis index according to the authentication node and the analysis dimension in the authentication process;
setting the weight of each risk analysis index, calculating risk information according to the risk analysis indexes and the weight, and establishing a risk analysis model;
acquiring a training sample, training the risk analysis model through the training sample, and acquiring the optimized weight of each risk analysis index to obtain a trained risk analysis model;
and acquiring the low-water footprint product authentication process information of the sample to be tested, inputting the information into the trained risk analysis model, and outputting the risk information of the sample to be tested in the low-water footprint product authentication process.
Optionally, the determining each risk analysis indicator according to the authentication node and the analysis dimension in the authentication process includes:
selecting at least one authentication node in the low water footprint product authentication process;
setting at least one analysis dimension;
and acquiring each risk analysis index according to the authentication node and the analysis dimensionality, and setting different attributes for the risk analysis indexes according to the influence on the overall risk degree.
Optionally, the authentication node includes part or all of an authentication application, a document review, a factory check, a data accounting, an authentication result evaluation and approval, a post-certification supervision, and a continuation application.
Optionally, the analysis dimension includes part or all of personnel, management, information, and technology.
Optionally, the processing for setting the weight of each risk analysis indicator includes:
obtaining objective weight of the risk analysis index;
acquiring expert weight of the risk analysis index;
and generating a combined weight according to the objective weight and the expert weight.
Optionally, the processing for obtaining the objective weight of the risk analysis indicator includes:
constructing an original data matrix for standardization processing, and constructing a dimensionless matrix;
and calculating the objective weight of the indexes by using the difference between the indexes.
Optionally, the establishing a risk analysis model includes:
multiplying the combination weight of the risk analysis indexes by the dimensionless matrix to obtain a risk weight output value of the risk analysis index corresponding to each product;
and calculating risk information according to each risk analysis index and the risk weight output value thereof.
The embodiment of the invention also provides a risk analysis device in the low-water footprint product authentication process, which comprises the following steps:
the flow acquiring unit is used for acquiring the authentication flow of the low-water footprint product;
the index determining unit is used for determining each risk analysis index according to the authentication nodes and the analysis dimensionality in the authentication process;
the model establishing unit is used for setting the weight of each risk analysis index, calculating risk information according to the risk analysis indexes and the weight and establishing a risk analysis model;
the training unit is used for acquiring a training sample, training the risk analysis model through the training sample, obtaining the optimization weight of each risk analysis index and obtaining the trained risk analysis model;
and the analysis unit is used for acquiring the low-water footprint product authentication process information of the sample to be tested, inputting the information into the trained risk analysis model, and outputting the risk information of the sample to be tested in the low-water footprint product authentication process.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the steps of the risk analysis method in the low-water footprint product authentication process.
An embodiment of the present invention further provides a computer readable medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the risk analysis method in the low-water footprint product authentication process.
The technical scheme of the invention has the following advantages:
according to the risk analysis method in the low-water footprint product authentication process, each risk analysis index is determined according to the authentication node and the analysis dimension of the authentication process of the low-water footprint product, a risk analysis model is established, the trained risk analysis model is obtained, and the determination of the risk information in the low-water footprint product authentication process of the sample to be tested is realized. In the scheme, qualitative and quantitative methods are combined to establish a low-water footprint product authentication risk analysis model; the method can solve the problems that risk elements are difficult to identify and the authentication risk is difficult to evaluate in the low-water footprint product authentication. The method has the advantages that a large amount of data are used as training samples, effective evaluation on low-water footprint product authentication can be realized, theoretical guidance is provided for subsequent low-water footprint product authentication widely implemented and low-water footprint authentication risk management and control are enhanced, certain guidance significance is provided for improving social public credibility of low-water footprint authentication marks, promoting supply side structural reform and consumption structure upgrade, evaluation and control on risks in the whole low-water footprint product authentication process can be realized, high scientificity, effectiveness and practicability are achieved, social public credibility of the low-water footprint authentication marks can be improved, and important significance is provided for building a water-saving society.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a specific example of a risk analysis method in the low water footprint product certification process in embodiment 1 of the present invention;
FIG. 2 is a flowchart of determining risk analysis indicators in embodiment 1 of the present invention;
FIG. 3 is a flowchart of obtaining objective weights of the risk analysis indicators in embodiment 1 of the present invention;
FIG. 4 is a schematic diagram of risk analysis indicators in the low-water footprint product certification process in embodiment 2 of the present invention;
FIG. 5 is a schematic block diagram of a specific example of a risk analysis device in the low water footprint product certification process in embodiment 2 of the present invention;
fig. 6 is a schematic diagram of a hardware structure of an electronic device executing the low-water footprint product authentication risk analysis method in embodiment 3 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1
The embodiment provides a risk analysis method in a low-water footprint product authentication process, which is used for analyzing risks in the low-water footprint product authentication process so as to determine whether risks and risk degrees exist in the authentication process of the low-water footprint product, and the method can be applied to control equipment such as a computer to execute the analysis method.
As shown in fig. 1, the risk analysis method in the low water footprint product certification process in the present embodiment includes the following steps:
s1, obtaining the authentication flow of the low water footprint product, wherein the flow is the flow for authenticating the low water footprint product, and the authentication flow may be different for different types of products. In this embodiment, the authentication process of the "low water footprint evaluation implementation rules" issued by the chinese quality authentication center is taken as a basis, and the authentication process includes the process stages of authentication application, document review, factory check, data accounting, authentication result evaluation and approval, after-certificate supervision, continued application, and the like.
And S2, determining each risk analysis index according to the authentication nodes and the analysis dimensions in the authentication process. A specific procedure of this step S2 is shown in fig. 2, and as shown in fig. 2, the step S2 includes:
s2-1, selecting an authentication node in the low water footprint product authentication process.
The authentication process in this embodiment refers to an authentication process of low-water footprint evaluation implementation rules issued by the chinese quality authentication center, and with the operability of the implementation and supervision of the authentication institution and the availability of index data as principles, under the suggestion of the authentication experts, seven authentication nodes are selected from the nodes in the authentication process of low-water footprint products for calculation, which are respectively authentication application, document review, factory check, data accounting, authentication result evaluation and approval, post-certification supervision, and continuation application. As another embodiment, only a part of the authentication nodes may be selected.
The authentication application refers to the fact that an enterprise submits an application for low-water footprint product authentication to an authentication institution; the document review refers to a verification task of water footprint review issued by project management personnel to form a verification group. The checking group leader is responsible for document review and reviews the application data and the certification document submitted by the enterprise to be evaluated; the factory inspection refers to that a certification authority selects and assigns capable personnel to form an inspection group on the basis that the file review meets the requirements or basically meets the requirements, a factory inspection plan is made based on the production flow and the characteristics of an enterprise, an enterprise to be inspected is informed seven working days in advance, and field inspection is carried out on the enterprise on schedule; the data accounting refers to the water footprint accounting of enterprises and products by water footprint evaluators according to related evaluation standards and specifications; the certification result evaluation and approval refers to that the certification authority comprehensively evaluates the field check result and the application data, and issues a water footprint evaluation certificate and/or an evaluation report to the application consignor after the evaluation is qualified; the supervision after obtaining the certificate is that after the enterprise passes the low water footprint certification evaluation of the certification authority and obtains the low water footprint mark, the certification authority carries out tracking evaluation for ensuring the continuous validity of the low water footprint mark within a certain time; the continuous application means that after the evaluation is completed, if the enterprise has the change of related content, the certification authority re-evaluates or confirms according to the changed content and the provided data, the report and the validity period of the certificate are still the original validity period after the change, if the certificate exceeds the validity period, the certificate is automatically invalidated, and the review is executed according to the new application.
The authentication nodes may have differences according to different products to be authenticated. The authentication node is reasonably set as required. The authentication nodes are the basis for quantitative analysis of the whole authentication process, and the risk in the whole process is judged by analyzing the nodes in the authentication process.
S2-2, setting analysis dimensions, in this embodiment, four dimensions are selected for analysis, which are: personnel, management, information, technology.
The personnel reflects personnel allocation and measures risk information of the certification authority in the aspect of personnel resource allocation in a certain link. Management refers to a management system, and whether a certification authority/enterprise has a perfect low-water footprint certification management system or not is measured. The information refers to information transfer, and the risk of timeliness and accuracy of the information transfer between an enterprise and an authentication mechanism and between an upper authentication link and a lower authentication link is measured. The technology refers to professional technology, and the professional technology of a certification authority/enterprise prepares risks when related certification business is processed.
Through the analysis of the four dimensions, the whole authentication process is measured. Different products can be analyzed by selecting proper dimension according to needs.
S2-3, obtaining each risk analysis index according to the authentication node and the analysis dimensionality, and setting different attributes for the risk analysis indexes according to the influence on the overall risk degree, wherein the attribute setting rule of the risk analysis indexes is as follows: and setting the risk points as plus and minus according to the influence of the risk points on the overall risk degree of the low-water footprint product authentication, wherein the larger the true value of the risk point with the attribute of plus represents the higher the risk, and the smaller the true value of the risk point with the attribute of minus represents the smaller the risk.
In this embodiment, according to the authentication nodes and the analysis dimensions, the risk analysis indexes in the authentication process of the low-water footprint product are constructed, and as shown in fig. 4, 41 risk points are selected as the risk analysis indexes.
And (3) respectively establishing evaluation standards for 41 risk analysis indexes: the risk index value which can be directly obtained adopts the true value; and (3) making a corresponding scoring standard for the risk index value which cannot be directly obtained, wherein the numerical range is 1-10, scoring the risk index value by an expert scoring method, and obtaining sample data for training and testing.
S3, setting the weight of each risk analysis index, calculating risk information according to the risk analysis indexes and the weight, and establishing a risk analysis model.
The weight in this embodiment is a combination weight, and is obtained by combining objective weight and expert weight. The objective weight refers to the weight of a risk analysis index calculated based on an entropy weighting method, the expert weight is obtained based on expert scoring, and the objective weight and the expert weight are fused to obtain the final combined weight.
The process of obtaining the objective weight of the risk analysis indicator is shown in fig. 3 as follows:
s3-1, constructing an original data matrix for standardization, and constructing a dimensionless matrix;
supposing that n products are provided, m risk analysis indexes are provided, and the jth index value of the ith certification product is recorded as aij(i =1,2, ⋯ n; j =1,2, ⋯, m), constituting an initial matrix a:
the missing data is interpolated by the arithmetic mean of the same type of authentication products in the same region.
Because the dimensions of the index data are not uniform, the following standardization needs to be performed on the initial matrix a: selecting a maximum and minimum standardization method to process index data with different attributes: and dividing the indexes into positive and negative indexes according to the influence of the indexes on the overall authentication risk and calculating by using different formulas. The formula is as follows:
wherein i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to m, sigma is the standard deviation of the original data of the index j, and c is the segmentation threshold of sigma and is the normalized value of the jth index of the ith product.
And S3-2, calculating objective weight of the indexes by using the difference between the indexes.
Calculating the specific gravity of the j item index value of the ith product
：
Wherein k is Boltzmann constant and has
. Calculating the weight:
therefore, according to the established hierarchical structure of the low-water footprint product authentication risk analysis indexes, the importance ranking is carried out on the risk analysis indexes in the low-water footprint product authentication process.
Wherein the process of obtaining the expert weight of the risk analysis index is as follows: and according to the low-water footprint product authentication risk analysis indexes, scoring the risk degrees of the 41 three-level indexes related to the authentication process by an expert scoring method, wherein the numerical range is 1-10, and calculating the expert weight of the risk analysis indexes.
In this step, expert weights are introduced for analysis to eliminate the effect of over-objective calculation results: according to the low-water footprint product authentication risk analysis indexes, the risk degree of each index related to the authentication process is scored by an expert scoring method, the numerical range is 1-10, the expert weight of the risk analysis indexes is calculated, objective influences are eliminated, and the result is more accurate.
After the objective weights and the expert weights are obtained, the combining weights may be generated according to the objective weights and the expert weights. And adding the obtained objective weight of each risk analysis index to the expert weight of the obtained risk analysis index in proportion to obtain the combination weight of the risk analysis indexes:
（7）
wherein wjIs the combined weight of index j, wHObjective weight as an indicator of risk analysis, wSAlpha and beta are objective weight adjusting coefficient and expert weight adjusting coefficient of the index j respectively.
After the combination weight is obtained, calculating risk information according to the risk analysis index and the weight, and establishing a risk analysis model comprises the following steps: multiplying the combination weight of the risk analysis indexes by the dimensionless matrix to obtain a risk weight output value of the risk analysis index corresponding to each product; and calculating risk information according to each risk analysis index and the risk weight output value thereof. The method comprises the following specific steps:
calculating risk information according to the risk analysis indexes and the weights, calculating a final output matrix and product authentication risk information, and recording a final calculation result matrix as B:
wherein i is more than or equal to 1 and less than or equal to n, j is more than or equal to 1 and less than or equal to m,
is the output value of the jth index of the ith product.
The Risk information in the product authentication process refers to authentication Risk (verification Risk Degree), and the authentication Risk of the ith product is calculated as follows:
thus, a risk analysis model can be constructed, and the optimal values of alpha and beta can be obtained through further training.
And S4, obtaining a training sample, training the risk analysis model through the training sample, obtaining the optimization weight of each risk analysis index, and obtaining the trained risk analysis model. Training the model by using training data, determining a satisfactory risk combination weight coefficient by changing the values of alpha and beta, and optimizing the w of a risk analysis indexHAnd wSAnd (4) obtaining a final low-water footprint product authentication risk analysis model.
In the step, the model is trained through a large amount of sample data, model optimization is carried out through changing the proportion of the objective weight and the expert weight in the combined weight in the risk analysis indexes, and therefore the risk analysis model in the low-water footprint product authentication process is obtained.
S5, acquiring the low-water footprint product authentication process information of the sample to be tested, inputting the information into the trained risk analysis model, and outputting the risk information of the sample to be tested in the low-water footprint product authentication process. After the risk analysis model is supervised, when a test sample is input, the risk degree corresponding to the test sample can be output, so that the risk in the multi-product authentication process is analyzed and evaluated, and the risk condition in the authentication process is objectively obtained.
The risk analysis method in the low-water footprint product authentication process in the embodiment evaluates risks in the low-water footprint product authentication process, constructs a low-water footprint product authentication process risk analysis model, and can solve the problems that risk elements in low-water footprint product authentication are difficult to identify and authentication risks are difficult to evaluate. The method has the advantages that a large amount of data are used as training samples, effective evaluation on low-water footprint product authentication can be achieved, theoretical guidance is provided for subsequent low-water footprint product authentication widely implemented and low-water footprint authentication risk management and control are enhanced, certain guiding significance is provided for improving social public credibility of low-water footprint authentication marks and promoting supply-side structural reform and consumption structure upgrade, and the method has important significance for building a water-saving society.
Example 2
As shown in fig. 4 and 5, the present embodiment provides a risk analysis device in the low water footprint product certification process, and fig. 4 is a schematic diagram of risk analysis indexes in the low water footprint product certification process in embodiment 2; fig. 5 is a functional block diagram of a risk analysis device in the low water footprint product certification process in this embodiment 2; the risk analysis device in the low water footprint product certification process includes:
a process obtaining unit 01, configured to obtain an authentication process of the low-water footprint product; the detailed description is given in S1 in example 1, and is not repeated here.
An index determining unit 02, configured to determine each risk analysis index according to an authentication node and an analysis dimension in the authentication process; the detailed description is given in S2 in example 1, and is not repeated here.
The model establishing unit 03 is configured to set a weight of each risk analysis index, calculate risk information according to the risk analysis index and the weight, and establish a risk analysis model; the details of the specific manner are shown in S in example 1, and are not described herein again. The establishing of the risk analysis model comprises the following steps: multiplying the combination weight of the risk analysis indexes by the dimensionless matrix to obtain a risk weight output value of the risk analysis index corresponding to each product; and calculating risk information according to each risk analysis index and the risk weight output value thereof.
The training unit 04 is used for obtaining a training sample, training the risk analysis model through the training sample, obtaining the optimization weight of each risk analysis index, and obtaining the trained risk analysis model; the detailed description is given in S4 in example 1, and is not repeated here.
And the analysis unit 05 is used for acquiring the low-water footprint product authentication process information of the sample to be tested, inputting the information into the trained risk analysis model, and outputting the risk information of the sample to be tested in the low-water footprint product authentication process. The detailed description is given in S5 in example 1, and is not repeated here.
The index determining unit 02 includes:
a first subunit, configured to select at least one authentication node in the low-water footprint product authentication procedure. The authentication node comprises part or all of authentication application, document review, factory check, data accounting, authentication result evaluation and approval, after-certificate supervision and application continuation.
A second subunit for setting at least one analysis dimension; the analysis dimension comprises part or all of personnel, management, information and technology.
And the third subunit is used for acquiring each risk analysis index according to the authentication node and the analysis dimensionality and setting different attributes for the risk analysis indexes according to the influence on the overall risk degree.
Wherein, the model establishing unit 03 includes:
the first weight calculating subunit is used for acquiring the objective weight of the risk analysis index;
the second weight calculation subunit is used for acquiring the expert weight of the risk analysis index;
and the combined weight generating subunit is used for generating combined weights according to the objective weights and the expert weights.
Wherein the first weight calculating subunit includes:
the matrix construction subunit is used for constructing an original data matrix for standardization processing and constructing a dimensionless matrix;
and the calculating subunit is used for calculating the objective weight of the index by using the difference between the indexes.
The risk analysis device in the low-water footprint product authentication process in the embodiment can solve the problems that risk elements are difficult to identify and authentication risks are difficult to evaluate in low-water footprint product authentication. The method has the advantages that a large amount of data are used as training samples, effective evaluation on low-water footprint product authentication can be achieved, theoretical guidance is provided for subsequent low-water footprint product authentication widely implemented and low-water footprint authentication risk management and control are enhanced, certain guiding significance is provided for improving social public credibility of low-water footprint authentication marks and promoting supply-side structural reform and consumption structure upgrade, and the method has important significance for building a water-saving society.
Example 3
Fig. 6 is a schematic diagram of a hardware structure of an electronic device for executing a low-water footprint product authentication risk analysis method according to an embodiment of the present invention, as shown in fig. 6, the device includes one or more processors 610 and a memory 620, and one processor 610 is taken as an example in fig. 6.
The apparatus for performing the above method may further include: an input device 630 and an output device 640.
The processor 610, the memory 620, the input device 630, and the output device 640 may be connected by a bus or other means, such as the bus connection in fig. 6.
The memory 620, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the processing methods of list item operations in the embodiments of the present application. The processor 610 executes various functional applications of the server and data processing by executing non-transitory software programs, instructions and modules stored in the memory 620, namely, implements the method in the above-described method embodiments.
The memory 620 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the processing apparatus operated by the list items, and the like. Further, the memory 620 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 620 optionally includes memory located remotely from the processor 610, which may be connected to the processing device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 630 may receive input numeric or character information and generate key signal inputs related to function control. The output device 640 may include a display device such as a display screen.
The one or more modules are stored in the memory 620 and, when executed by the one or more processors 610, perform the methods shown in fig. 1-3.
The product can execute the method provided by the embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. Details of the technique not described in detail in the present embodiment may be specifically referred to the related description in the embodiments shown in fig. 1 to 3.
The embodiment of the invention also provides a non-transitory computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the processing method of the list item operation in any method embodiment. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a Random Access Memory (RAM), or the like.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1-7 are implemented when the program is executed by the processor.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A risk analysis method in a low water footprint product certification process is characterized by comprising the following steps:
obtaining an authentication process of the low-water footprint product;
determining each risk analysis index according to the authentication node and the analysis dimension in the authentication process;
setting the weight of each risk analysis index, calculating risk information according to the risk analysis indexes and the weight, and establishing a risk analysis model;
acquiring a training sample, training the risk analysis model through the training sample, and acquiring the optimized weight of each risk analysis index to obtain a trained risk analysis model;
and acquiring the low-water footprint product authentication process information of the sample to be tested, inputting the information into the trained risk analysis model, and outputting the risk information of the sample to be tested in the low-water footprint product authentication process.
2. The method of claim 1, wherein determining risk analysis indicators according to authentication nodes and analysis dimensions in the authentication process comprises:
selecting at least one authentication node in the low-water footprint product authentication process;
setting at least one analysis dimension;
and acquiring each risk analysis index according to the authentication node and the analysis dimensionality, and setting different attributes for the risk analysis indexes according to the influence on the overall risk degree.
3. The method of claim 2, wherein the authentication node comprises part or all of an authentication application, document review, factory verification, data accounting, authentication result evaluation and approval, post-certification supervision, continuation application.
4. The method of claim 2 or 3, wherein the analysis dimension comprises part or all of personnel, management, information, technology.
5. The method according to claim 1,2 or 3, wherein the process of setting the weight of each risk analysis indicator comprises:
obtaining objective weight of the risk analysis index;
acquiring expert weight of the risk analysis index;
and generating a combined weight according to the objective weight and the expert weight.
6. The method according to claim 5, wherein the process of obtaining the objective weight of the risk analysis indicator comprises:
constructing an original data matrix for standardization processing, and constructing a dimensionless matrix;
and calculating the objective weight of the indexes by using the difference between the indexes.
7. The method of claim 6, wherein the establishing a risk analysis model comprises:
multiplying the combination weight of the risk analysis indexes by the dimensionless matrix to obtain a risk weight output value of the risk analysis index corresponding to each product;
and calculating risk information according to each risk analysis index and the risk weight output value thereof.
8. A risk analysis device in a low water footprint product certification process, comprising:
the flow acquiring unit is used for acquiring the authentication flow of the low-water footprint product;
the index determining unit is used for determining each risk analysis index according to the authentication nodes and the analysis dimensionality in the authentication process;
the model establishing unit is used for setting the weight of each risk analysis index, calculating risk information according to the risk analysis indexes and the weight and establishing a risk analysis model;
the training unit is used for acquiring a training sample, training the risk analysis model through the training sample, obtaining the optimization weight of each risk analysis index and obtaining the trained risk analysis model;
and the analysis unit is used for acquiring the low-water footprint product authentication process information of the sample to be tested, inputting the information into the trained risk analysis model, and outputting the risk information of the sample to be tested in the low-water footprint product authentication process.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1-7 are implemented when the program is executed by the processor.
10. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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Application publication date: 20210212 |