CN115936512A - Target demand-based weapon equipment design scheme evaluation method and system - Google Patents
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Abstract
The invention provides a method and a system for evaluating a weapon equipment design scheme based on target requirements, wherein the method comprises the following steps: firstly, defining the core indexes and the domains of the core indexes of weaponry, and establishing an index space; establishing a target requirement set of weapon equipment design, namely determining what weapon equipment is needed and what index requirement is; then inviting the domain experts to evaluate the attribute of each scheme, and describing the uncertainty of the scheme attribute by using a reliability distribution function instead of replacing the scheme attribute by using a determined value; then inputting the solution into the system to calculate the reliability of each solution belonging to the target demand set as the matching degree of the solution and the target demand; and finally, selecting a scheme. The invention solves the technical problems that the scheme does not evaluate the target requirements and the uncertainty of the scheme index (attribute) is not fully considered.
Description
Technical Field
The invention relates to the field of equipment evaluation demonstration, in particular to a method and a system for evaluating a weapon equipment design scheme based on target requirements.
Background
The military and the strong nations all over the world are tightening the research and development of required weaponry for the battle scene which may happen in the future. The development of weaponry requires the selection of a reasonable design that cannot be effectively evaluated. The evaluation of the design scheme of the weaponry not only needs evaluators to be proficient in the principle and the use requirements of the evaluators, but also needs a set of scientific and reasonable evaluation method.
At present, a multi-criterion (attribute) decision method is adopted for scheme evaluation, namely, a plurality of normalized indexes (attributes) in the scheme are aggregated in a certain mode to obtain a comprehensive index, and the scheme is selected according to the size of the comprehensive index. However, the method only focuses on the comprehensive sequencing of the schemes and does not consider whether the schemes can meet the target requirements or not. For example, in the invention patent "a method for optimizing a product design scheme" with publication number CN103577888A, an index system for product evaluation is first established, normalization processing is performed on index (attribute) values, then weights of the indexes are calculated by combining an AHP method and an entropy weight method, then optimal index values and worst index values are respectively substituted to obtain optimal schemes and worst schemes, finally, comprehensive values are calculated by an ideal solution, and scheme ranking is obtained by comparing the comprehensive values. For another example, in the invention patent "a comprehensive evaluation method of grid structure safety based on entropy weight method" with publication number CN103107535A, evaluation indexes of grid structure safety are determined first, then weights of the indexes are calculated by using the entropy weight method, index values of a certain grid are input and normalized, finally, a comprehensive value is obtained by using a weighting aggregation operator, and the grade of the grid structure safety performance is divided according to the comprehensive value. For another example, the invention patent publication No. CN 10756680A "power distribution network reliability evaluation method based on AHP and entropy weight method" first establishes an evaluation index of power distribution network reliability, then uses the AHP and entropy weight method to synthesize the weight of the integrated calculation index, then inputs the normalized index value of a certain power distribution network, and uses a weighting aggregation operator to obtain a comprehensive value, which reflects the reliability of the power distribution network.
The Multiple attribute decision method based on interval number, such as Multiple attribute decision-making method based on the probability sorting method based on the number of the sub-intervals and ordered weighted aggregation operators of the interactive neutral numbers, first uses the interval number to represent the uncertainty of the scheme index, then uses the aggregation operator to obtain the integrated interval value, and finally uses the interval number sorting method to sort the schemes. The interval number sorting method tries to convert the uncertainty problem into a certain deterministic problem, such as a median sorting method, a sorting method based on expectation and variance, a sorting method based on the probability degree, and the like, but the method is unstable, and the sorting results obtained by different interval sorting methods are often different. Therefore, the multi-attribute decision method based on the interval number does not change the essential defects, i.e. only the comprehensive comparison is focused, and the target requirements are not considered.
As can be seen from the detailed implementation of the foregoing prior art scheme, the foregoing prior art is used to aggregate information of multiple dimensions into one dimension by using a certain aggregation operator, so as to facilitate comparison and sorting of schemes. However, this approach ignores the target requirement, and ordering first is not necessarily an alternative, nor ordering last is necessarily an alternative. The degree of freedom of practical problems is large, the processing mode of The average ignores The diversity and uniqueness of The practical problems, the selected result often has larger deviation from The true outcome, such as The case described in The literature (The end of average: how to win in The world of The Chongstandardization), the pilot cabin is designed by The average height of The pilot, and all pilots are not suitable on The contrary.
In summary, the existing scheme evaluation technology has the technical problems that no target requirements are paid attention to and the uncertainty of the scheme attributes is not fully considered.
Disclosure of Invention
The technical problem to be solved by the invention is how to solve the technical problem in the prior art that target requirements are not fully considered and the uncertainty of indexes (attributes) in a scheme is not fully considered.
The invention adopts the following technical scheme to solve the technical problems: the method for evaluating the weapon equipment design scheme based on the target requirement comprises the following steps:
s1, acquiring weapon equipment indexes to establish a weapon equipment index vector space;
s2, acquiring target demand data of the design scheme to establish a target demand set of the weaponry, wherein the target demand data comprises: benefit indexes and cost indexes, and a target demand set is contained in a weapon equipment index vector space;
s3, evaluating the index parameters of each design scheme, and representing the uncertainty of the index in each design scheme by using a reliability distribution function;
s4, calculating the reliability that each design scheme meets a target requirement set by using a preset matching degree processing logic so as to represent the matching degree of the design schemes;
and S5, judging the uncertainty of the acquired design scheme according to the matching degree of the current design scheme by utilizing a preset matching degree threshold interval so as to reduce the uncertainty of the design scheme, and circularly executing the step S4 and the step S5 so as to obtain a target demand conforming scheme.
The method takes the target requirement as the guide, selects the scheme most suitable for the target requirement, not only fully considers the diversity and uniqueness of the actual problem, but also fully considers the uncertainty of the scheme index (attribute), and selects the appropriate design scheme by calculating the matching degree of the scheme and the target requirement set. The matching degree in the invention is essentially the subjective possibility that the scheme meets the target requirement, the uncertainty of the scheme index is fully considered, and the appropriate design scheme is selected by calculating the reliability that the scheme meets the target requirement.
In a more specific technical solution, step S1 includes:
s11, setting the ith index as X i ，(i＝1,2,…,n)；
S12, obtaining a value-taking domain of the ith index through conversion: [ L ] i ,U i ]，0≤L i <U i In the present embodiment, U i May be + ∞;
s13, according to the value-taking domain, representing a weapon equipment index vector space by using the following logic:
A:[L 1 ,U 1 ]×[L 2 ,U 2 ]×...×[L n ,U n ]。
in a more specific technical solution, step S2 includes:
s21, setting index X 1 Target requirement of [ g ] 1 ,g 1 ']，X 2 Target requirement of [ g ] 2 ,g 2 ']，…，X n The target requirements are:
[g n ,g n ']
wherein, g i Is X i Corresponding target floor value (floor value means no worse than this value), g i ' is X i Corresponding optimal values (i =1,2, \8230;, n);
s22, the following logic is used for representing the benefit index:
g i '＝U i ；
s22, representing the cost type index by the following logic:
g i '＝L i ；
s23, forming a target demand set omega by using the target demands of the benefit index and the cost index g ：
[g 1 ,g 1 ']×[g 2 ,g 2 ']×...×[g n ,g n ']。
The target requirement set of the invention conforms to the thinking characteristics of people. Due to the limited rationality of people, the standard measurement which can be given by people and is usually only satisfied or not satisfied, and the condition that the target is achieved or not achieved is avoided, so that the condition that in the classical utility theory, people need to give continuous and accurate utility values, and in reality, people hardly give accurate and continuous utility values is avoided.
In a more specific technical solution, in step S3, in the current design solution, the following logic fitting is used to obtain a reliability distribution function for each index (attribute) evaluation, so as to characterize uncertainty of not less than 2 indexes in the design solution:
Φ 1 (X 1 )，Φ 2 (X 2 )，…，Φ n (X n )。
the method disclosed by the invention is used for tightly matching the target requirements, fully considering the uncertainty, paying attention to the diversity and uniqueness of the scheme indexes, and searching the scheme which best meets the target requirements through reliability calculation. The invention fully considers the uncertainty of the attribute, adopts the reliability distribution function to describe the uncertainty of the scheme attribute, and better accords with the actual situation compared with the prior art.
In a more specific technical solution, in step S4, according to the index uncertainty, the following logic is used to calculate the reliability that each design solution meets the target requirement:
wherein X 1 ,X 2 ,...,X s Is a profitability index (the index value is as large as possible), X s+1 ,X s+2 ,...,X n Is a cost-based index (the smaller the index value is, the better), 1<s<n is the same as the formula (I). For the interval type index, it is possible to convert to these two index processes.
In a more specific technical solution, in step S4, the reliability of the solution meeting the target requirement is obtained by using the following logic processing according to equation (1):
α * ＝(1-Φ 1 (g 1 ))∧(1-Φ 2 (g 2 ))...∧(1-Φ s (g s ))∧
Φ s+1 (g s+1 )∧Φ s+2 (g s+2 )...∧Φ n (g n )。
in a more specific technical solution, in step S5, it is determined whether the matching degree of the current design scheme is close to a preset matching degree threshold.
In a more specific technical solution, in step S5, when the matching degree of the current design scheme is close to a preset matching degree threshold, it is necessary to reduce the uncertainty of the design scheme on the target requirement boundary, and then the design scheme is put into the system again for calculation;
in a more specific technical solution, in step S5, when the matching degree of the current design scheme is close to a preset matching degree threshold, and when the matching degree is close to a preset selection parameter, the design scheme is selected as a target requirement compliance scheme.
In a more specific aspect, a system for evaluating a target requirements-based weaponry design includes:
the index space construction module is used for acquiring weapon equipment indexes and establishing a weapon equipment index vector space;
the target demand set construction module is used for acquiring target demand data of the design scheme so as to establish a target demand set of weapon equipment, wherein the target demand data comprises: the target demand set construction module is connected with the target demand set construction module;
the scheme evaluation module is used for carrying out scheme evaluation on the index parameters of each design scheme, representing the index uncertainty in each design scheme by using a reliability distribution function, and is connected with the index space construction module and the target demand set construction module;
the matching degree acquisition module is used for calculating the reliability of each design scheme meeting the target requirement set by utilizing preset reliability processing logic so as to represent the matching degree of the design scheme, and the matching degree acquisition module is connected with the scheme evaluation module;
the requirement conforming scheme selecting module is used for judging the uncertainty degree of the acquired design scheme according to the matching degree of the current design scheme by utilizing a preset matching degree threshold so as to reduce the uncertainty of the design scheme, executing the step S4 and the step S5 in a circulating manner so as to obtain a target requirement conforming scheme, and the requirement conforming scheme selecting module is connected with the matching degree acquiring module.
Compared with the prior art, the invention has the following advantages: the method takes the target requirement as the guide, selects the scheme most suitable for the target requirement, not only fully considers the diversity and uniqueness of the actual problem, but also considers the uncertainty of the scheme attribute, and selects the appropriate design scheme by calculating the reliability (matching degree) of the scheme meeting the target requirement. The matching degree in the invention is essentially the subjective possibility that the scheme meets the target requirement, the uncertainty of the attribute of the scheme is fully considered, and a proper design scheme is selected by calculating the matching degree of the scheme and the target requirement set.
The target requirement set of the invention conforms to the thinking characteristics of people. Due to the limited rationality of people, the standard measurement which can be given by people and is usually only satisfied or not satisfied reaches the target or does not reach the target is avoided, the situation that in the classical utility theory, people need to give continuous and accurate utility values, and in reality, people can hardly give accurate and continuous utility values is avoided.
The method provided by the invention is used for tightly matching the target requirements, fully considering the uncertainty, paying attention to the diversity and uniqueness of the problem, and searching the scheme which best meets the target requirements through reliability calculation. The method fully considers the uncertainty of the attribute, adopts the reliability distribution function to describe the uncertainty of the attribute of the scheme, and is more in line with the actual situation compared with the prior art.
The invention solves the technical problems that the scheme does not fully consider the uncertainty of the scheme in the prior art for evaluating the target demand which is not fastened.
Drawings
FIG. 1 is a schematic diagram of the method for evaluating the design of weaponry based on target requirements of embodiment 1 of the present invention;
FIG. 2 is a two-dimensional schematic of the matching of the solution of example 1 of the present invention with the target requirements;
FIG. 3 is a chart of the confidence level of the CEP of a missile of a specific type in example 2 of the invention;
FIG. 4 is a plot of the distribution of confidence in CEPs for a particular type of missile according to example 2 of the present invention;
FIG. 5a is a graph of a reliability distribution function of a front radar scattering cross section RCS in the solution A of embodiment 3 of the present invention;
fig. 5b is a graph of a reliability distribution function of the maximum transient angular velocity ω in the solution a according to embodiment 3 of the present invention;
FIG. 5c is a graph of a confidence distribution function of the target detection distance D in scenario A of embodiment 3 of the present invention;
FIG. 5d is a plot of a belief distribution function of the effective range R of the missile in scenario A of example 3 of the present invention;
FIG. 6a is a graph of a reliability distribution function of a front radar cross section RCS in the solution B of embodiment 3 of the present invention;
FIG. 6B is a graph of a confidence distribution function of the maximum instantaneous angular velocity ω in the solution B in embodiment 3 of the present invention;
FIG. 6c is a graph of a confidence distribution function of the target detection distance D in the solution B of embodiment 3 of the present invention;
FIG. 6d is a graph of a belief distribution function of the effective range R of the missile in the scenario B of example 3 of the present invention;
FIG. 7a is a graph of a reliability distribution function of a front radar scattering cross section RCS in the solution C of embodiment 3 of the present invention;
fig. 7b is a graph of a reliability distribution function of the maximum instantaneous angular velocity ω in the C scheme of embodiment 3 of the present invention;
FIG. 7C is a graph of a confidence distribution function of the target detection distance D in the solution C of embodiment 3 of the present invention;
FIG. 7d is a plot of a belief distribution function of the effective range R of the missile in scenario C of example 3 of the present invention;
fig. 8a is a graph of a reliability distribution function of a front radar scattering cross section RCS in a C scenario after index update according to embodiment 3 of the present invention;
fig. 8b is a graph of a reliability distribution function of the maximum instantaneous angular velocity ω in the C scenario after the index update of embodiment 3 of the present invention;
fig. 8C is a graph of a reliability distribution function of the target detection distance D in the scheme C after the index update of embodiment 3 of the present invention;
fig. 8d is a graph of a reliability distribution function of the effective range R of the missile in the C scheme after the index update of embodiment 3 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. 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.
Example 1
As shown in FIG. 1, the method for evaluating the design scheme of the weapon equipment based on the target requirement provided by the invention comprises the following steps:
s1, establishing a weapon equipment index space;
in this embodiment, let X 1 ,X 2 ,...,X n Core target (attribute) for certain type of weaponry, where X 1 ,X 2 ,...,X s Is a profitability index (the index value is as large as possible), X s+1 ,X s+2 ,...,X n Is a cost-based index (the smaller the index value is, the better), 1<s<n is the same as the formula (I). For interval type indexes, the two types of index processing can be converted;
in this embodiment, the index vector space a: x i Is the ith index, (i =1,2, \8230;, n), and the actual value range can be converted to [ L ] as the value range i ,U i ]，0≤L i <U i ，U i Can be taken as + ∞, and the index vector space can be expressed as A: [ L 1 ,U 1 ]×[L 2 ,U 2 ]×...×[L n ,U n ]；
S2, establishing a target demand set of weapon equipment;
in the present embodiment of the present invention,target demand set Ω g ：
Let X 1 Target requirement of [ g ] 1 ,g 1 ']，X 2 Target requirement of [ g ] 2 ,g 2 ']，…，X n Target requirement of [ g ] n ,g n ']. Wherein g is i Is X i The corresponding target floor value (i =1,2, \8230;, n), meaning that it cannot be worse than this value. For the benefit index, g i '＝U i (ii) a For cost index, g i '＝L i . The target requirements of all indexes form a target requirement set omega g ：[g 1 ,g 1 ']×[g 2 ,g 2 ']×...×[g n ,g n ']；
S3, evaluating the schemes, and depicting the uncertainty of the indexes of each design scheme by using a reliability distribution function;
in this embodiment, the confidence level (Belief Degree) represents the strength with which a human believes that an event will occur. The confidence level is between 0 and 1, and the higher the confidence level is, the higher the possibility that the person subjectively feels the event occurs is represented. According to the literature (Uncertainty Theory: branch of Human Uncertainty Modeling, A Branch of Mathematics for Modeling Human Uncertainty Theory), the essential difference between probability and confidence is the difference in the degree of multiplication. Roughly speaking, the product metric of probability theory is "multiplication", and the product metric of confidence is "minimizer", i.e.:
P r {A×B}＝P r {A}×P r {B}，M{A×B}＝M{A}∧M{B}
wherein, P r Is a measure of probability and M is a measure of confidence.
In the present example, according to the principle of the belief function in the literature (uncertain Theory: branch of Human Uncertainty Modeling: A Branch of Mathematics for Modeling Humanan Uncertainty Theory): for any real number x, the belief distribution function Φ for the uncertain variable ξ is defined as:
Φ(x)＝M{ξ≤x}
in this embodiment, what weaponry is needed, i.e., what target requirements are met. After a target demand set of the weaponry is established, inviting experts in corresponding fields, evaluating indexes (attributes) of the weaponry under each scheme, and representing the evaluation condition of the experts on each unknown index by using a reliability distribution function;
in this embodiment, it is assumed that, in a certain design weapon equipment plan, the reliability distribution function evaluated by the expert for each index (attribute) is Φ 1 (X 1 )，Φ 2 (X 2 )，…，Φ n (X n )；
S4, calculating the reliability of each design scheme meeting the target requirement, and representing the matching degree of the scheme;
as shown in FIG. 2, in this embodiment, the schema is a two-dimensional schematic diagram of the matching of the target requirement set. The invention takes the reliability that the scheme meets the target requirement as the matching degree of the scheme and the target requirement set. And calculating the matching degree of the scheme and the target demand set, wherein the scheme with the matching degree closest to 1 is the optimal scheme.
The confidence level that a certain scheme meets the target demand set is as follows:
s5, determining whether the matching degree is close to a threshold interval of a preset matching degree, in this embodiment, a value interval of the preset matching degree threshold includes but is not limited to: [0.45,0.55];
s6, if yes, reducing uncertainty of the scheme on a target demand boundary;
and S7, if not, selecting the scheme with the highest matching degree, wherein in the embodiment, the threshold meeting the requirement can adopt, for example: 1.
example 2
As shown in fig. 3, in this embodiment, the Circle Probability Error (CEP) of a certain missile is an unknown variable, the reliability distribution function is shown in fig. 1, and if the real number x =50, the reliability of the corresponding CEP ≦ 50 is 0.8. It can be seen that for any real number x, there is a corresponding confidence.
How to generate a reliability distribution function, taking the design of a certain type of missile as an example, inviting an expert to evaluate the CEP of a certain scheme of missile, wherein the evaluation process is as follows:
asking: asking you to see what is the minimum CEP of the missile after the design has been successfully implemented?
Answering: 100m.
Asking: how many meters do you think the CEP of this type of missile is at its maximum?
Answering: 300m.
Asking: what is your confidence level of 120 meters or less?
Answering: 0.05.
asking: what do you think of a reliability of 140 m or less?
Answering: 0.1.
asking for: what do you think are the credibility of 160 meters or less?
Answering: 0.15.
asking for: what is you think of a confidence level of 180 m or less?
Answering: 0.2.
asking: what is you think of a reliability of 200 m or less?
Answering: 0.5.
asking: what do you think of a reliability of 220 m or less?
Answering: 0.8.
asking: what do you think of a reliability of 240 meters or less?
Answering: 0.9.
asking: what do you think of a reliability of 260 meters or less?
Answering: 0.95.
asking: what do you think of a reliability of 280 meters or less?
Answering: 0.98.
as shown in fig. 4, in the present embodiment, discrete determination data are summarized: (100,0), (120,0.15), (140,0.2), (160,0.25), (180,0.3), (200,0.35), (220,0.4), (240,0.6), (260,0.8), (280,0.9), (300,1). The judgment data for collating the CEP of the missile is shown in Table 1: TABLE 1 confidence distribution of CEPs
From the data in table 1, a confidence distribution function is generated by high-order function interpolation, see fig. 4.
Example 3
Taking the demonstration of a certain type of fighter plane design scheme as an example:
firstly, the battle scene that the fighter may participate in the future is determined according to mission so as to determine what fighter is needed. The long-distance air combat of the fighter has four core indexes: front RCS, maximum instantaneous angular velocity ω,5m 2 Target detection distance D, effective range R of the missile. Suppose that the future battle scene needs the long-distance air battle of a fighter to reach the following index requirements:
①RCS≤0.1m 2 ；②ω≥0.48rad/s；③D≥200km；④R≥150km
at present, three design schemes A, B and C need to demonstrate and select the optimal scheme:
(1) Confidence that A plan meets target requirements
And (3) inviting the expert to evaluate each index in the scheme A, wherein discrete evaluation data are shown in a table 2:
confidence distributions of various indices in the scheme of Table 2A
As shown in fig. 5a to 5d, in this embodiment, the reliability distribution function of each index in the a scheme is fitted according to the evaluation data of the expert.
The credibility that the scheme A meets the target requirement is as follows:
α A * ＝Φ RCS (0.1)∧(1-Φ ω (0.48))∧(1-Φ D (200))∧(1-Φ R (150))
＝0.2∧(1-0.2)∧(1-0.7)∧(1-0.3)＝0.2
(2) Confidence that B plan meets target requirements
And (3) inviting the expert to evaluate each index in the B scheme, wherein discrete evaluation data are shown in a table 3:
confidence distribution of various indexes in scheme of Table 3B
As shown in fig. 6a to 6d, the confidence distribution function of each index in the B scheme is fitted according to the expert data evaluation.
The confidence level that the scheme B meets the target requirement is as follows:
α B * ＝Φ RCS (0.1)∧(1-Φ ω (0.48))∧(1-Φ D (200))∧(1-Φ R (150))
＝0.8∧(1-0.1)∧(1-0.1)∧(1-0.1)＝0.8
(3) Confidence that C-plan meets target requirements
And (3) inviting the expert to evaluate each index in the scheme C, wherein discrete evaluation data are shown in a table 3:
confidence distributions of various indexes in the scheme of Table 4C
As shown in fig. 7a to 7d, in the present embodiment, a reliability distribution function of each index in the C scenario is fitted according to the evaluation data of the expert.
The credibility that the scheme C meets the target requirement is as follows:
α C * ＝Φ RCS (0.1)∧(1-Φ ω (0.48))∧(1-Φ D (200))∧(1-Φ R (150))
＝0.7∧(1-0.2)∧(1-0.1)∧(1-0.5)＝0.5
whether the scheme C meets the target is very uncertain, and after the uncertainty that the index R in the scheme C meets the target requirement needs to be reduced in a key mode, the matching degree is calculated. By introducing more information to the iterative evaluation, the evaluation data of the index R is updated as follows:
adjusted confidence distributions for index R in the scheme of Table 5C
| |
100 | 110 | 115 | 120 | 123 | 126 | 129 | 134 | 141 | 150 | 160 |
| Reliability of service | 0 | 0.1 | 0.2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 | 1 |
As shown in fig. 8a to 8d, in the present embodiment, the index updates the reliability distribution function of the C-scenario.
The reliability of recalculating the solution C meeting the target requirements is:
α C * ＝Φ RCS (0.1)∧(1-Φ ω (0.48))∧(1-Φ D (200))∧(1-Φ R (150))
＝0.7∧(1-0.2)∧(1-0.1)∧(1-0.1)＝0.7
and comparing, the scheme B best meets the target requirement, and preferentially selecting the scheme B. The scheme ordering is B > C > A.
In summary, the invention takes the target requirement as the guide, selects the scheme most suitable for the target requirement, not only fully considers the diversity and uniqueness of the actual problem, but also considers the uncertainty of the scheme index (attribute), and selects the appropriate design scheme by calculating the matching degree of the scheme and the target requirement set. The matching degree in the invention is essentially the subjective possibility that the scheme meets the target requirement, the uncertainty of the scheme attribute is fully considered, and the proper design scheme is selected by calculating the reliability of the scheme meeting the target requirement.
The target demand set of the invention conforms to the thinking characteristics of people. Due to human rationality, a human can give a criterion measure that is usually only satisfactory or unsatisfactory, either to reach or not to reach a goal.
The method provided by the invention is used for tightly matching the target requirements, fully considering the uncertainty, paying attention to the diversity and uniqueness of the scheme indexes, and searching the scheme which best meets the target requirements through reliability calculation. The invention fully considers the uncertainty of the attribute, adopts the reliability distribution function to describe the uncertainty of the scheme attribute, and better accords with the actual situation compared with the prior art.
The invention solves the technical problems that the target requirements are not fastened and the technical problem that the scheme is not ensured is not fully considered in the prior art.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for target demand based assessment of weaponry design solutions, the method comprising:
s1, acquiring weapon equipment indexes to establish a weapon equipment index vector space;
s2, acquiring target demand data of the design scheme to establish a target demand set of the weapon equipment, wherein the target demand data comprises: a profitability index and a cost-based index, the target demand set contained in the weaponry equipment index vector space;
s3, evaluating the index parameters of each design scheme, and representing the uncertainty of the index in each design scheme by using a reliability distribution function;
s4, calculating the reliability of each design scheme meeting the target requirement by using preset reliability processing logic so as to represent the matching degree of the design schemes;
and S5, judging and obtaining the uncertainty of the design scheme according to the matching degree of the current design scheme by utilizing a preset matching degree threshold interval so as to reduce the uncertainty of the design scheme, and executing the step S4 and the step S5 in a circulating manner so as to obtain a target demand conforming scheme.
2. The method for evaluating a target demand-based weaponry design scenario of claim 1, wherein step S1 includes:
s11, setting the ith index as X i ，(i＝1,2,…,n)；
S12, obtaining a value-taking domain of the ith index through conversion: [ L ] i ,U i ]，0≤L i <U i ；
S13, according to the value-taking domain, expressing the weapon equipment index vector space by using the following logic:
A:[L 1 ,U 1 ]×[L 2 ,U 2 ]×...×[L n ,U n ]。
3. the method for evaluating a target demand-based weaponry design scenario of claim 1, wherein step S2 includes:
s21, setting index X 1 Target requirement of [ g ] 1 ,g 1 ']，X 2 Target requirement of [ g ] 2 ,g 2 ']，…，X n The target requirements are:
[g n ,g n ']
wherein, g i Is X i Corresponding target baseline values (i =1,2, \8230;, n), g i ' is X i The corresponding optimal value;
s22, representing the benefit index by using the following logic:
g i '＝U i ；
s23, representing the cost type index by the following logic:
g i '＝L i ；
s23, forming the target demand set omega by using the target demands of the benefit index and the cost index g ：[g 1 ,g 1 ']×[g 2 ,g 2 ']×...×[g n ,g n ']。
4. The method for evaluating a target requirement-based weaponry design solution of claim 1, wherein in step S3, a confidence distribution function is obtained for each attribute evaluation using the following logic fit in the current design solution to characterize not less than 2 index uncertainties in the design solution:
Φ 1 (X 1 )，Φ 2 (X 2 )，…，Φ n (X n )。
5. the method for evaluating target-demand-based weaponry design solutions of claim 1 wherein, in step S4, the confidence level that each of the design solutions meets target demands is calculated based on the target uncertainty using the following logic:
in the formula, X 1 ,X 2 ,...,X s Is a benefit index, X s+1 ,X s+2 ,...,X n Is a cost-type index, 1<s<n is the same as the formula (I). For the section type index, the two kinds of index processing can be converted.
6. The method for evaluating a target-requirement-based weaponry design scenario of claim 5, wherein in step S4, the confidence that the scenario meets the target requirement is obtained using the following logic:
7. the method of claim 1, wherein in step S5, it is determined whether the degree of matching of the current design approaches a preset threshold degree of matching.
8. The method of claim 1, wherein in step S5, when the degree of matching of the current design approaches a preset degree of matching threshold, the uncertainty parameter of the design on the target requirement boundary is reduced and the system calculation is re-performed.
9. The method for evaluating a target requirement-based weaponry design choices according to claim 1, wherein in step S5, when the degree of matching of the current design choice approaches a preset degree of matching threshold and when the degree of matching approaches a preset selection parameter, the design choice is selected as the target requirement compliance choice.
10. A system for target demand based assessment of weaponry design solutions, the system comprising:
the index space construction module is used for acquiring weapon equipment indexes and establishing a weapon equipment index vector space;
a target demand set construction module, configured to acquire target demand data of a design solution, so as to establish a target demand set of weapons equipment, where the target demand data includes: the target demand set is contained in the weapon equipment index vector space, and the target demand set construction module is connected with the target demand set construction module;
the scheme evaluation module is used for carrying out scheme evaluation on the index parameters of each design scheme and representing the index uncertainty in each design scheme by using a reliability distribution function, and is connected with the index space construction module and the target demand set construction module;
the matching degree acquisition module is used for calculating the reliability of each design scheme meeting the target requirement by utilizing preset reliability processing logic so as to represent the matching degree of the design scheme, and is connected with the scheme evaluation module;
the requirement conforming scheme selecting module is used for judging and obtaining the uncertainty of the design scheme according to the matching degree of the current design scheme by utilizing a preset matching degree threshold value so as to reduce the uncertainty of the design scheme, and circularly executing the step S4 and the step S5 so as to obtain a target requirement conforming scheme, wherein the requirement conforming scheme selecting module is connected with the matching degree obtaining module.
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|---|---|---|---|---|
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Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113204924A (en) * | 2021-05-28 | 2021-08-03 | 中国人民解放军军事科学院评估论证研究中心 | Complex problem oriented evaluation analysis method and device and computer equipment |
-
2022
- 2022-12-12 CN CN202211590030.3A patent/CN115936512A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113204924A (en) * | 2021-05-28 | 2021-08-03 | 中国人民解放军军事科学院评估论证研究中心 | Complex problem oriented evaluation analysis method and device and computer equipment |
Non-Patent Citations (2)
| Title |
|---|
| BAODING LIU: "Extreme value theorems of uncertain process with applicationto insurance risk model", 《SOFT COMPUT》, 25 September 2012 (2012-09-25), pages 550 - 556 * |
| 张天鹏;刘铁林;高萍;: "基于聚类分析和证据推理的装备体系能力评估与分析", 军事运筹与***工程, no. 04, pages 53 - 60 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116796202A (en) * | 2023-07-17 | 2023-09-22 | 上海朗晖慧科技术有限公司 | Equipment data matching method based on big data and abnormal data processing system |
| CN116796202B (en) * | 2023-07-17 | 2024-06-04 | 上海朗晖慧科技术有限公司 | Equipment data matching method based on big data and abnormal data processing system |
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