CN117933832B - Index weight evaluation method for spacecraft ground equivalence test - Google Patents
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Abstract
The invention provides an index weight evaluation method for spacecraft ground equivalence tests, which comprises the steps of obtaining test evaluation results of target attributes for an index cluster to be verified, which is composed of first indexes belonging to the same upper layer index, and generating an interval judgment matrix to determine interval weight vectors; acquiring an interval evaluation result of the target attribute of the second index of the lowest level; and determining an optimal value weight evaluation result of each target attribute of each first index by combining a foreground theory. The method converts the interval weight of each index into the optimal value weight based on the objective function with the maximum comprehensive prospect value, can search in the interval weight vector to obtain the objective weight evaluation result which meets the preference of a decision maker to the greatest extent, and is easier to accept and approve by the decision maker, so that the optimal index weight value search in the objective index interval weight range is realized, and compared with the traditional method for evaluating the index weight by directly counting the number value, the evaluation accuracy of the method is relatively reliable, and the evaluation risk can be effectively reduced.
Description
Technical Field
The invention relates to the technical field of space-based equipment, in particular to an index weight evaluation method for a spacecraft ground equivalence test.
Background
Before the spacecraft is in orbit, an on-orbit test can be simulated and developed through ground comprehensive means such as simulation analysis, complex space environment equivalence, semi-physical test and the like, however, in practice, the situations of over-simplified simulation test, insufficient test environment construction, insufficient accompanying test equipment capability and the like often exist. Therefore, before the ground equivalent test of the spacecraft is carried out, the defects of the ground equivalent test need to be analyzed, and the carrying-out effect of the equivalent test is ensured. For the ground equivalent test of the spacecraft, the quantitative evaluation mode of the compartment type is more suitable for the ground equivalent test evaluation of the spacecraft; if the interval evaluation is directly combined with the evaluation model, the evaluation of the ground equivalent test can show stronger uncertainty. For this, the obtained interval evaluation needs to be converted into a value evaluation. In the field of decision making/evaluation, the prospect theory is more in line with the preference behavior of people when facing problems in practice. Currently, many documents are used for calculating the benefit/loss value of the special evaluation number relative to the reference point in the foreground theory by constructing different scoring functions to realize the magnitude comparison between the special evaluation numbers such as the Bithagoras fuzzy number, the interval intuitionistic fuzzy number and the like. However, the profit/loss value obtained by the method can not reflect the visual preference of a decision maker in practice, so that the reliability of index weight evaluation of the spacecraft ground equivalent test by the related technology is low, and the evaluation risk is increased.
Disclosure of Invention
The invention aims to provide an index weight evaluation method for a spacecraft ground equivalent test, which is used for improving evaluation reliability and reducing evaluation risk.
The invention provides an index weight evaluation method for spacecraft ground equivalence test, which comprises the following steps: acquiring preset indexes of a plurality of levels corresponding to a spacecraft ground equivalent test; aiming at an index cluster to be verified, which is formed by each first index belonging to the same upper index in each level, obtaining a test evaluation result of each target attribute in the index cluster to be verified, wherein the test evaluation result is used for indicating the importance degree among indexes; the test evaluation result is determined based on a preset first evaluation standard; generating an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes; determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the interval judgment matrix; acquiring an interval evaluation result corresponding to each target attribute of each second index of the lowest level; the interval evaluation result is determined based on a preset second evaluation standard; determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and constraint conditions; wherein the objective function is maximally determined based on the integrated foreground value.
Further, based on the interval judgment matrix, the step of determining the interval weight vector corresponding to each target attribute in the index cluster to be verified comprises the following steps: if the interval judgment matrix of each target attribute in the index cluster to be verified meets a preset consistency condition, decomposing each interval judgment matrix into an upper limit decomposition matrix and a lower limit decomposition matrix; determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on an upper limit decomposition matrix and a lower limit decomposition matrix corresponding to each interval judgment matrix; for each target attribute, the interval weight vector includes a weight upper limit value and a weight lower limit value corresponding to the target attribute of each first index.
Further, the step of determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result and a preset objective function and constraint conditions includes: determining a target reference point corresponding to each target attribute of each second index based on each interval evaluation result; wherein the target reference point comprises: a positive reference point and a negative reference point; determining, for each second index, a benefit value of each section evaluation result of each target attribute relative to a negative reference point and a loss value relative to a positive reference point under the second index based on a target reference point and a plurality of section evaluation results corresponding to each target attribute of the second index; and determining an optimal value weight evaluation result of each target attribute of each first index through a preset objective function and constraint conditions based on the interval weight vector, the loss value and the gain value corresponding to each target attribute of each second index.
Further, the target attributes include: test completion and/or test confidence.
The invention provides an index weight evaluation device for spacecraft ground equivalence test, which comprises: the first acquisition module is used for acquiring preset indexes of a plurality of levels corresponding to the spacecraft ground equivalent test; the second acquisition module is used for acquiring a test evaluation result of each target attribute in the index cluster to be verified, which is used for indicating the importance degree among the indexes, aiming at the index cluster to be verified formed by each first index belonging to the same upper index in each level; the test evaluation result is determined based on a preset first evaluation standard; the generating module generates an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes; the first determining module is used for determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the interval judgment matrix; the third acquisition module is used for acquiring an interval evaluation result corresponding to each target attribute of each second index of the lowest level; the interval evaluation result is determined based on a preset second evaluation standard; the second determining module is used for determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and constraint conditions; wherein the objective function is maximally determined based on the integrated foreground value.
Further, the first determining module is further configured to: if the interval judgment matrix of each target attribute in the index cluster to be verified meets a preset consistency condition, decomposing each interval judgment matrix into an upper limit decomposition matrix and a lower limit decomposition matrix; determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on an upper limit decomposition matrix and a lower limit decomposition matrix corresponding to each interval judgment matrix; for each target attribute, the interval weight vector includes a weight upper limit value and a weight lower limit value corresponding to the target attribute of each first index.
Further, the second determining module is further configured to: determining a target reference point corresponding to each target attribute of each second index based on each interval evaluation result; wherein the target reference point comprises: a positive reference point and a negative reference point; determining, for each first indicator, a benefit value of each section evaluation result of each target attribute relative to a negative reference point and a loss value relative to a positive reference point under the first indicator based on a target reference point and a plurality of section evaluation results corresponding to each target attribute of the first indicator; and determining an optimal value weight evaluation result of each target attribute of each first index through a preset objective function and constraint conditions based on the interval weight vector, the loss value and the gain value corresponding to each target attribute of each first index.
Further, the target attributes include: test completion and/or test confidence.
The invention provides electronic equipment, which comprises a processor and a memory, wherein the memory stores machine executable instructions which can be executed by the processor, and the processor executes the machine executable instructions to realize the index weight evaluation method of the spacecraft ground equivalence test.
The invention provides a machine-readable storage medium storing machine-executable instructions that, when invoked and executed by a processor, cause the processor to implement the index weight assessment method of the spacecraft ground equivalent test of any one of the above.
According to the index weight evaluation method for the spacecraft ground equivalent test, preset indexes of a plurality of layers corresponding to the spacecraft ground equivalent test are obtained; aiming at an index cluster to be verified, which is formed by each first index belonging to the same upper index in each level, obtaining a test evaluation result of each target attribute in the index cluster to be verified, wherein the test evaluation result is used for indicating the importance degree among indexes; the test evaluation result is determined based on a preset first evaluation standard; generating an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes; determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the interval judgment matrix; acquiring an interval evaluation result corresponding to each target attribute of each second index of the lowest level; the interval evaluation result is determined based on a preset second evaluation standard; determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and constraint conditions; wherein the objective function is maximally determined based on the integrated foreground value. The method converts the interval weight of each index into the optimal value weight based on the objective function with the maximum comprehensive prospect value, can search in the interval weight vector to obtain the objective weight evaluation result which meets the preference of a decision maker to the greatest extent, and is easier to accept and approve by the decision maker, so that the optimal index weight value search in the objective index interval weight range is realized, and compared with the traditional method for evaluating the index weight by directly counting the number value, the evaluation accuracy of the method is relatively reliable, and the evaluation risk can be effectively reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an index weight evaluation method for a spacecraft ground equivalent test provided by an embodiment of the invention;
FIG. 2 is a schematic diagram of a value weight of the completion and confidence of each index equivalent test according to an embodiment of the present invention;
Fig. 3 is a schematic structural diagram of an index weight evaluation device for a spacecraft ground equivalent test according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Before the spacecraft enters orbit, the on-orbit test can be simulated and developed through ground comprehensive means such as simulation analysis, complex space environment equivalence, semi-physical test and the like, so that the left shift of test identification work is realized, the test development cost is reduced, and the test completion period is shortened. The ground equivalent test method is particularly suitable for testing performance indexes of spacecrafts with large on-orbit development difficulty and difficult touch edge and bottom detection. However, in practice, there are often cases where the simulation test is too simplified, the test environment is not sufficiently constructed, and the capability of accompanying test equipment is not sufficient. Therefore, if the ground equivalent test is directly carried out, the identification effect of the spacecraft can be greatly reduced, and even an identification personnel can give an unreasonable identification conclusion. Therefore, before the ground equivalent test of the spacecraft is carried out, the ground equivalent test needs to be evaluated, so that the defect of the equivalent test is analyzed, and the carrying effect of the equivalent test is ensured.
The evaluation framework considering the spacecraft ground equivalent test is a tree structure formed by multiple layers of indexes. Therefore, the same as the current mainstream evaluation mode, the evaluation index weight of each same layer needs to be determined so as to measure the relative importance among indexes. At present, a point value weighting method combining subjective and objective is used for determining the index weight. The method is not limited to obtaining the optimal combination between the index subjective weight and the index objective weight by means of minimizing the dispersion, and the like, so that the weight difference caused by the subjective weight and the objective weight giving method is balanced. And correcting the subjective weight by using the objective weight. However, for the ground equivalent test of the spacecraft, compared with the point value type evaluation mode, the interval type quantitative evaluation mode is more suitable for the ground equivalent test evaluation of the spacecraft.
However, if the interval weight is directly combined with the evaluation model, the evaluation of the ground equivalent test presents stronger uncertainty. In this case, the obtained section weight needs to be converted into a value weight. Theoretically, conversion to real numbers is only possible based on a certain number of reference intervals. Common transformation methods include an analysis method, a probability method, and the like. However, the purpose of this type of method is to achieve an intuitive comparison between the interval numbers and is not suitable for weight conversion. In the decision/evaluation field, the usual theory of expected effects cannot explain the irrational behaviour of the decision maker. In contrast, the prospect theory is more consistent with the preference behavior of people when facing problems in practice. In recent years, the prospect theory has been widely applied in the fields of asset configuration, traffic management, multi-attribute decision, emergency decision and the like. However, the conventional foreground theory cannot calculate the gain/loss value of the interval type evaluation result relative to the interval reference point. But the profit/loss value obtained by the method can not reflect the visual preference of a decision maker in practice, is difficult to accept and approve by the decision maker, and obviously deviates from the original purpose of the foreground theory, so that the index weight evaluation reliability of the spacecraft ground equivalent test by the related technology is lower, and the evaluation risk is increased. Based on the above, the embodiment of the invention provides an index weight evaluation method for a spacecraft ground equivalent test, and the technique can be applied to the application of evaluating the index weight of the spacecraft ground equivalent test.
In order to facilitate understanding of the present embodiment, first, an index weight evaluation method for a spacecraft ground equivalent test disclosed in the present embodiment is described, as shown in fig. 1, where the method includes the following steps:
Step S102, acquiring preset indexes of a plurality of layers corresponding to a spacecraft ground equivalent test;
The number of the preset indexes of each level may be one or more; the number of specific levels and the number of preset indexes contained in each level can be set according to actual requirements. In actual implementation, when the spacecraft ground equivalent test needs to be evaluated, preset indexes of a plurality of levels corresponding to the spacecraft ground equivalent test can be acquired first, for example, three levels are provided, wherein the first level is an index M, the second level comprises indexes M1 and M2 which are downward divided by the index M, and the third level comprises indexes M11 and M12 which are downward divided by the index M1, indexes M21 and M22 which are downward divided by the index M2, and the like.
Step S104, aiming at an index cluster to be verified, which is formed by each first index belonging to the same upper index in each level, obtaining a test evaluation result of each target attribute in the index cluster to be verified, wherein the test evaluation result is used for indicating the importance degree among indexes; the test evaluation result is determined based on a preset first evaluation standard;
For convenience of explanation, taking the first level including the index M and the index N as an example, the index of the second level corresponding to the index M includes M1 and M2, the index of the second level corresponding to the index N includes N1 and N2, and for each first index belonging to the same upper level index in each level, obtaining a to-be-verified index cluster composed of each first index; for example, M1 and M2 in the second level belong to the same upper level index M, and N1 and N2 in the second level belong to the same upper level index N, so that M1 and M2 form an index cluster to be verified; n1 and N2 form another index cluster to be verified, test evaluation results of importance degrees among the indication indexes of each target attribute in each index cluster to be verified are obtained, and the target attribute can be set according to actual verification requirements, and can comprise test completion degree, test confidence degree and the like. The test evaluation result can be determined through a test based on the first evaluation standard, and an objective result is obtained instead of a manually set result, and the test evaluation result can represent the importance degree among different first indexes under the target attribute; the first evaluation criterion may be a related international universal test criterion, a related domestic universal test criterion, or the like in the art.
Step S106, generating an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes;
In actual implementation, after obtaining the test evaluation result corresponding to each target attribute in each to-be-verified index cluster, a corresponding interval judgment matrix may be generated according to each test evaluation result, for example, taking the to-be-verified index cluster formed by M1 and M2 as an example, where for each target attribute, the interval judgment matrix corresponding to the to-be-verified index cluster includes a lower importance limit and an upper importance limit corresponding to M1 relative to itself, M1 relative to M2, M2 relative to M1, and M2 relative to itself, respectively.
Step S108, determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the interval judgment matrix;
After the interval judgment matrix is generated, an interval weight vector corresponding to each target attribute in the index cluster to be verified can be determined according to the interval judgment matrix, and in the interval weight vector, the weight corresponding to each first index is an interval range.
Step S110, obtaining an interval evaluation result corresponding to each target attribute of each second index of the lowest level; the interval evaluation result is determined based on a preset second evaluation standard;
for example, continuing with the example in step S102, each of the second indexes of the lowest level is the indexes M11 and M12, and the indexes M21 and M22 in the third level, and the interval evaluation result of each of the target attributes of the four indexes may be obtained, where the interval evaluation result may be determined based on a second evaluation criterion, and the second evaluation criterion may be a related international universal test criterion, a related domestic universal test criterion, or the like in the field.
Step S112, determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and constraint conditions; wherein the objective function is maximally determined based on the integrated foreground value.
The foreground theoretical model mainly comprises reference points, a cost function and a decision weight function. The reference point is the benchmark of the difference between the expected and actual results of the judgment decision maker. In general, the reference point may be selected from zero, median, expected value of the index, and the like. The form of the cost function is shown as a formula (1):
In the middle of Is a foreground value; Is that Deviation from the reference pointIs of a size of (a) and (b). When (when)When, the benefit is represented. When (when)When, loss is indicated;、 the risk attitude parameters respectively represent the sensitivity degree to benefits and losses; representing risk avoidance parameters.
Statistical results of Tversky et al are generally taken。
The decision weight function adopts an inverse S-shaped curve function to replace a linear function, and a calculation formula is shown as formula (2):
In the method, in the process of the invention, 、Respectively represent the ith index weightDecision weights of the corresponding positive and negative foreground values.、Representing the risk attitude, i.e. the degree of curvature of the decision weight function, in the face of the return and loss, respectively. Statistical results of Tversky et al are generally taken、。
Combining the cost function and the decision weight function, calculating the comprehensive prospect value of the scheme is shown as a formula (3):
Wherein V j is the comprehensive prospect value of the jth scheme; 、 Positive and negative foreground values of the jth scheme under the ith index respectively. For the present embodiment, different schemes may be understood as different evaluation results of the spacecraft ground equivalent test.
In actual implementation, after the interval weight vector, the interval evaluation result, the preset objective function and the constraint condition are obtained, the optimal value weight evaluation result of each objective attribute of each first index can be determined based on the objective function with the maximum comprehensive prospect value and the preset constraint condition.
According to the index weight evaluation method for the spacecraft ground equivalent test, preset indexes of a plurality of levels corresponding to the spacecraft ground equivalent test are obtained; aiming at an index cluster to be verified, which is formed by each first index belonging to the same upper index in each level, obtaining a test evaluation result of each target attribute in the index cluster to be verified, wherein the test evaluation result is used for indicating the importance degree among indexes; the test evaluation result is determined based on a preset first evaluation standard; generating an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes; determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the interval judgment matrix; acquiring an interval evaluation result corresponding to each target attribute of each second index of the lowest level; the interval evaluation result is determined based on a preset second evaluation standard; determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and constraint conditions; wherein the objective function is maximally determined based on the integrated foreground value. The method converts the interval weight of each index into the optimal value weight based on the objective function with the maximum comprehensive prospect value, can search in the interval weight vector to obtain the objective weight evaluation result which meets the preference of a decision maker to the greatest extent, and is easier to accept and approve by the decision maker, so that the optimal index weight value search in the objective index interval weight range is realized, and compared with the traditional method for evaluating the index weight by directly counting the number value, the evaluation accuracy of the method is relatively reliable, and the evaluation risk can be effectively reduced.
The embodiment of the invention also provides another index weight evaluation method for spacecraft ground equivalence test, which is realized on the basis of the method of the embodiment, and comprises the following steps:
step one, acquiring preset indexes of a plurality of layers corresponding to a spacecraft ground equivalence test;
Step two, aiming at an index cluster to be verified, which is formed by each first index belonging to the same upper index in each level, obtaining a test evaluation result of each target attribute in the index cluster to be verified, wherein the test evaluation result is used for indicating the importance degree among indexes; the test evaluation result is determined based on a preset first evaluation standard;
In this embodiment, the target attributes generally include: the test completion and/or the test confidence, preferably, can be evaluated to analyze the deficiency of the equivalence test and ensure the development effect of the equivalence test.
Step three, generating an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attributes of other first indexes;
Ground equivalent test evaluation of spacecraft there may be multiple co-layer indexes on different levels. In order to obtain the index weight with higher reliability, the invention firstly adopts an interval hierarchical analysis (INTERVAL ANALYTICAL HIERARCHY Process, IAHP) method to obtain a reasonable interval of the index weight. Based on a preset first evaluation standard, a section judgment matrix can be given to a certain level index system with n first indexes according to a 1-9 scale method, wherein the section judgment matrix comprises the following steps:
In the method, in the process of the invention, 。A lower limit value of importance of the ith index relative to the jth index; The upper limit value of the importance of the i-th index with respect to the j-th index is represented.
If the interval judgment matrix of each target attribute in the index cluster to be verified meets the preset consistency condition, decomposing each interval judgment matrix into an upper limit decomposition matrix and a lower limit decomposition matrix;
The preset consistency condition can be strong consistency and the like; judging matrix A for the above interval if and only if any There isWhen A has strong consistency. Wherein for the followingAnd (3) withThere is. In view of this, whether a has strong consistency can be taken as a criterion. If the interval judgment matrix does not meet the judgment criterion, the interval judgment matrix is usually directly reported to be wrong so as to prompt that the acquired test evaluation result is abnormal.
Step five, determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on an upper limit decomposition matrix and a lower limit decomposition matrix corresponding to each interval judgment matrix; for each target attribute, the interval weight vector comprises a weight upper limit value and a weight lower limit value corresponding to the target attribute of each first index;
Will be Dividing into matrix according to upper and lower limits of intervalAnd (3) with; Wherein,Is based onA lower limit decomposition matrix composed of each importance lower limit value; is based on An upper limit decomposition matrix composed of each importance upper limit value. The normalized eigenvector corresponding to the maximum eigenvalue of the upper limit decomposition matrix can be solved by referring to the solving mode in the related artAnd a first coefficient c, solving a standardized feature vector corresponding to the maximum feature value of the lower limit decomposition matrixAnd a second coefficient d; wherein,Each vector in the n first indexes respectively represents an upper-limit standardized feature vector corresponding to each first index; Each vector in the n first indexes respectively represents a lower-limit standardized feature vector corresponding to each first index; the first coefficient c and the second coefficient d are calculated by the formula (5).
Then the feature vector is normalized according to the interval judgment matrix ANormalized feature vectorThe first coefficient c and the second coefficient d, and the interval weight vector of each first index in the n indexes is obtained as follows:
。
It can be seen that the weight corresponding to each first index is a section composed of a weight lower limit value and a weight upper limit value.
Step six, obtaining an interval evaluation result corresponding to each target attribute of each second index of the lowest level; the interval evaluation result is determined based on a preset second evaluation standard;
Step seven, determining a target reference point corresponding to each target attribute of each second index based on each interval evaluation result; wherein the target reference point comprises: a positive reference point and a negative reference point;
For n same-layer indexes of the equipment equivalent evaluation test, set And (3) the comprehensive evaluation matrix corresponding to the K interval evaluation results of each index is shown as a formula (6) for the K interval evaluation results corresponding to the p index.
In order to avoid overlarge drop of a decision maker caused by taking the optimal and worst schemes as positive and negative reference points, positive and negative ideal points are selected as the positive and negative reference points by combining an ideal point method (YOPSIS) and a gray correlation analysis method. The specific calculation is shown in formula (7):
(7)
step eight, determining, for each second index, a benefit value of each section evaluation result of each target attribute relative to a negative reference point and a loss value relative to a positive reference point under the second index based on a target reference point and a plurality of section evaluation results corresponding to each target attribute of the second index;
For calculation of the cost function, most documents currently compare the sizes of different interval numbers by setting different scoring functions so as to convert the interval numbers into real numbers. However, the score function is too abstract, so that the profit and loss values in the cost function are calculated, which results in that the decision maker cannot intuitively feel the profit and loss, thereby deviating from the original purpose of the foreground theory. Thus, a calculation method for giving a differential evaluation gain and loss value is required in principle. Is provided with The p index of the reference point is the k interval estimation result corresponding to the p indexFor example, the calculation methods of the profit (Rew) and Loss (Loss) values are given in table 1.
TABLE 1 loss and gain values for reference points and interval evaluation values in different positional relationships
Thus, the calculation formulas of the positive foreground value and the negative foreground value of the evaluation result of the jth interval under the ith index are as follows:
In the method, in the process of the invention, Representing the evaluation result of the jth interval under the ith indexA benefit value relative to a negative reference point; representing the evaluation result of the jth interval under the ith index Loss value relative to positive reference point.
And step nine, determining an optimal value weight evaluation result of each target attribute of each first index through a preset objective function and constraint conditions based on the interval weight vector, the loss value and the gain value corresponding to each target attribute of each second index.
The IAHP can be considered to have a higher confidence in the resulting weight interval vector. Therefore, the section weight of each index is converted into the value weight which is more in line with the expectations of a decision maker by combining the scheme comprehensive prospect value calculation method given by the formula (3). Searching each index weight value in each index weight interval by taking the maximum comprehensive prospect value of each scheme as an objective function, and constructing an index weight search model as follows:
wherein V is the comprehensive prospect value of the evaluation results of j intervals.
To further understand the above embodiment, a day-based detection apparatus is taken as an example, and the evaluation is determined by the completion and confidence of the test, and each evaluation index has a two-dimensional evaluation attribute. Therefore, the completion and confidence of the equivalent evaluation test of each capability index of the equipment are required to be jointly developed and analyzed.
Generating a corresponding interval number judgment matrix according to the obtained test evaluation result:
(10)
According to strong consistency criteria And judging the consistency of the interval judgment matrix. Judging matrix by intervalThe results are shown in Table 2 for illustration. To avoid redundancy, the remaining matrix、、、、、、The consistency test results of (2) are not specifically shown. The result shows that all the interval judgment matrixes meet. Therefore, the comparison results of the index weights of the same layer all meet the requirement of the continuity test.
Table 2 section count judgment matrixConsistency check of (a)
Will beDividing into matrix according to upper and lower limits of intervalAnd (3) with. Respectively solving the standardized eigenvectors corresponding to the maximum eigenvalues of the decomposition matrix as、; The two corresponding coefficients are、; The interval weight of index C 1~C3 is. Similarly, the interval weights of the remaining indexes can be obtained as shown in table 3.
TABLE 3 interval weights for the remaining class indicators
Based on the actual test results of the equipment index layer and the second evaluation criteria, the section evaluation results of the equipment capability layer index (corresponding to the second index) of the lowest level are obtained, and the obtained second index test evaluation results are shown in table 4.
Table 4 test evaluation results of each index
The positive and negative reference points of the completion and confidence of each index equivalent test can be obtained by the formula (7) and the table 4 respectively:
(11)
The loss and gain values of each index evaluation result with respect to the positive and negative reference points can be calculated according to table 1 and equation (8), and the results are shown in table 5.
TABLE 5 loss and gain values for each index evaluation results relative to the positive and negative reference points
The ground equivalent test evaluation of the spacecraft has 4 groups of same-layer evaluation indexes including equipment overall evaluation and equipment capacity evaluation. Then to optimize the evaluation of the overall equipping equivalence test, model form (9) is refined to:
In the method, in the process of the invention, The method comprises the steps of performing equivalent evaluation on equipment performance, equivalent evaluation on system applicability and equivalent evaluation on in-service applicability; Is that The 9 index weights of the next level;、 representing risk attitudes in the face of returns and losses, respectively; representing risk avoidance parameters.
Taking out. Thus, according to the formula (12), the completion degree and the confidence weight of each index are optimized by adopting an optimization algorithm, and then the target weight vector of each index in the same layer, which is evaluated by the spacecraft ground equivalent test, can be obtained、、、. The maximum comprehensive prospect values after optimizing are-0.2597 and-0.1887 for the equivalent test completion degree and the confidence degree respectively. The indices as shown in fig. 2 equivalent the test completion and confidence value weights.
The invention combines the interval analytic hierarchy process and the foreground theory to provide an index weight determining method for the spacecraft ground equivalence test. Generating a section judgment matrix according to an evaluation result of relatively accurate section type importance among the acquired indexes; judging the rationality of the interval judgment matrix according to the strong consistency criterion; and finally, calculating the weight interval vector of each index by an interval characteristic root method. Because of the interval evaluation mode, the obtained weight interval can be considered to have higher credibility. In the theory framework of the foreground theory, the search model of the index weight is established by maximizing the comprehensive foreground value, so that the conversion from the index interval weight to the value weight is realized. Therefore, the interval weight of the index can be converted into the accurate value weight according to the preference of the decision maker, so that the index weighting can be more biased to the decision preference of the decision maker in a reasonable range, and the problem that the interval weight cannot be directly converted into the value weight is solved.
The method is based on the acquired interval evaluation results of all the attributes of the index; selecting positive and negative ideal points as positive and negative reference points by combining an ideal point method and a gray correlation analysis method; finally, starting from the position relation between the intervals, the calculation of the gain/loss value of the index interval evaluation result is realized according to theoretical analysis. Therefore, the abstract scoring function can be prevented from being constructed, the gain/loss value of the index interval assessment result relative to the reference point can be directly obtained, the fusion of interval assessment and the foreground theory is realized, and the fitting degree of the calculation result and the preference of a decision maker in reality is improved.
The embodiment of the invention provides an index weight evaluation device for spacecraft ground equivalence test, as shown in fig. 3, the device comprises:
the first obtaining module 50 is configured to obtain preset indexes of a plurality of levels corresponding to a spacecraft ground equivalent test;
A second obtaining module 51, configured to obtain, for each first index belonging to the same upper layer index in each level, a test evaluation result for indicating importance degree between indexes of each target attribute in the index cluster to be verified; the test evaluation result is determined based on a preset first evaluation standard;
the generation module 52 generates an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes;
a first determining module 53, configured to determine an interval weight vector corresponding to each target attribute in the to-be-verified index cluster based on the interval judgment matrix;
A third obtaining module 54, configured to obtain an interval evaluation result corresponding to each target attribute of each second index of the lowest level; the interval evaluation result is determined based on a preset second evaluation standard;
A second determining module 55, configured to determine an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, the preset objective function and the constraint condition; wherein the objective function is maximally determined based on the integrated foreground value.
According to the index weight evaluation device for the spacecraft ground equivalence test, the interval weight of each index is converted into the optimal value weight based on the objective function with the maximum comprehensive prospect value, the objective weight evaluation result meeting the preference of a decision maker to the greatest extent can be obtained by searching in the interval weight vector, and the objective weight evaluation result is easier to accept and accept by the decision maker, so that the optimal index weight value searching in the objective index interval weight range is realized, compared with the traditional method of directly evaluating the index weight, the evaluation accuracy is relatively reliable, and the evaluation risk can be effectively reduced.
Further, the first determining module is further configured to: if the interval judgment matrix of each target attribute in the index cluster to be verified meets a preset consistency condition, decomposing each interval judgment matrix into an upper limit decomposition matrix and a lower limit decomposition matrix; determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on an upper limit decomposition matrix and a lower limit decomposition matrix corresponding to each interval judgment matrix; for each target attribute, the interval weight vector includes a weight upper limit value and a weight lower limit value corresponding to the target attribute of each first index.
Further, the second determining module is further configured to: determining a target reference point corresponding to each target attribute of each second index based on each interval evaluation result; wherein the target reference point comprises: a positive reference point and a negative reference point; determining, for each first indicator, a benefit value of each section evaluation result of each target attribute relative to a negative reference point and a loss value relative to a positive reference point under the first indicator based on a target reference point and a plurality of section evaluation results corresponding to each target attribute of the first indicator; and determining an optimal value weight evaluation result of each target attribute of each first index through a preset objective function and constraint conditions based on the interval weight vector, the loss value and the gain value corresponding to each target attribute of each first index.
Further, the target attributes include: test completion and/or test confidence.
The index weight evaluation device for the spacecraft ground equivalent test provided by the embodiment of the invention realizes the same principle and the same technical effect as those of the embodiment of the index weight evaluation method for the spacecraft ground equivalent test, and for the sake of brief description, the corresponding content in the embodiment of the index weight evaluation method for the spacecraft ground equivalent test can be referred to.
The embodiment of the present invention further provides an electronic device, as shown in fig. 4, where the electronic device includes a processor 130 and a memory 131, where the memory 131 stores machine executable instructions that can be executed by the processor 130, and the processor 130 executes the machine executable instructions to implement the index weight evaluation method for the above-mentioned spacecraft ground equivalent test.
Further, the electronic device shown in fig. 4 further includes a bus 132 and a communication interface 133, and the processor 130, the communication interface 133, and the memory 131 are connected through the bus 132.
The memory 131 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 133 (which may be wired or wireless), and may use the internet, a wide area network, a local network, a metropolitan area network, etc. Bus 132 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 4, but not only one bus or type of bus.
The processor 130 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in processor 130. The processor 130 may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), etc.; but may also be a digital signal Processor (DIGITAL SIGNAL Processor, DSP), application Specific Integrated Circuit (ASIC), field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 131, and the processor 130 reads the information in the memory 131, and in combination with its hardware, performs the steps of the method of the foregoing embodiment.
The embodiment of the invention also provides a machine-readable storage medium, which stores machine-executable instructions that, when being called and executed by a processor, cause the processor to implement the index weight evaluation method for the spacecraft ground equivalent test, and specific implementation can be seen in the method embodiment and will not be described herein.
The computer program product of the index weight evaluation method for spacecraft ground equivalent test provided by the embodiment of the invention comprises a computer readable storage medium storing program codes, wherein the instructions included in the program codes can be used for executing the method described in the method embodiment, and specific implementation can be seen from the method embodiment and will not be repeated here.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (8)
1. An index weight evaluation method for a spacecraft ground equivalent test is characterized by comprising the following steps:
Acquiring preset indexes of a plurality of levels corresponding to a spacecraft ground equivalent test;
Aiming at an index cluster to be verified, which is formed by each first index belonging to the same upper index in each level, obtaining a test evaluation result of each target attribute in the index cluster to be verified, wherein the test evaluation result is used for indicating the importance degree among indexes; wherein the test evaluation result is determined based on a preset first evaluation standard;
generating an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes;
Determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the interval judgment matrix;
acquiring an interval evaluation result corresponding to each target attribute of each second index of the lowest level; wherein the interval evaluation result is determined based on a preset second evaluation standard;
determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and constraint conditions; wherein the objective function is maximally determined based on the comprehensive prospect value;
The step of determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and a constraint condition comprises the following steps:
Determining a target reference point corresponding to each target attribute of each second index based on each interval evaluation result; wherein the target reference point comprises: a positive reference point and a negative reference point; the positive reference point and the negative reference point are determined based on an ideal point method and a gray correlation analysis method;
for n second indexes of the same layer in the spacecraft ground equivalence test, set up And for the kth interval evaluation result corresponding to the p second index, the comprehensive evaluation matrix corresponding to the K interval evaluation results of each second index is shown in the following formula:
According to the following formula, positive ideal points and negative ideal points are selected as positive reference points and negative reference points respectively by combining an ideal point method and a gray correlation analysis method:
；
determining, for each second index, a benefit value of each section evaluation result of each target attribute relative to a negative reference point and a loss value relative to a positive reference point under the second index according to the following formula based on a target reference point and a plurality of section evaluation results corresponding to each target attribute of the second index;
；；
In the method, in the process of the invention, Representing the evaluation result of the jth interval under the ith indexA benefit value relative to a negative reference point; representing the evaluation result of the jth interval under the ith index Loss value relative to positive reference point; the loss valueAnd the benefit valueCalculating the relative position relation between the target reference point and the interval evaluation value;
Is provided with The p index of the target reference point is the k interval evaluation result corresponding to the p second index isThe calculation method of the loss value and the gain value of the target reference point and the interval evaluation value under different position relations is as follows:
When (when) At the time of cost, the benefit value isThe loss value is 0; or benefit, benefit value 0, loss value；
When (when)At the time of cost, the profit value is 0, and the loss value is; Or benefit value of; The loss value is 0;
When (when) At the time of cost, the benefit value isThe loss value is 0; or benefit, benefit value is 0, loss value is；
When (when)At the time of cost, the profit value is 0, and the loss value is; Or benefit value ofThe loss value is 0;
When (when) At the time of cost, the benefit value isLoss value of; Or benefit value ofLoss value of；
When (when)When the cost type is adopted, the profit value is 0, and the loss value is 0; benefit, benefit value is 0, loss value is 0;
Determining an optimal value weight evaluation result of each target attribute of each first index through a preset objective function and constraint conditions based on the interval weight vector and the loss value and the gain value corresponding to each target attribute of each second index;
The index weight search model corresponding to the objective function is as follows:
；
wherein V is the comprehensive prospect value of the j interval evaluation results; 、 Respectively represent the ith index weight Decision weights of the corresponding positive and negative foreground values;、 representing risk attitudes in the face of returns and losses, respectively; c is a first coefficient; d is a second coefficient; And Respectively represent the ith index weightUpper-normalized feature vectors and lower-normalized feature vectors of (a).
2. The method of claim 1, wherein determining an interval weight vector corresponding to each target attribute in the to-be-verified index cluster based on the interval judgment matrix comprises:
if the interval judgment matrix of each target attribute in the index cluster to be verified meets a preset consistency condition, decomposing each interval judgment matrix into an upper limit decomposition matrix and a lower limit decomposition matrix;
Determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the upper limit decomposition matrix and the lower limit decomposition matrix corresponding to each interval judgment matrix; for each target attribute, the interval weight vector includes a weight upper limit value and a weight lower limit value corresponding to the target attribute of each first index.
3. The method of claim 1, wherein the target attribute comprises: test completion and/or test confidence.
4. An index weight evaluation device for spacecraft ground equivalence test, characterized in that the device comprises:
the first acquisition module is used for acquiring preset indexes of a plurality of levels corresponding to the spacecraft ground equivalent test;
The second acquisition module is used for acquiring a test evaluation result of each target attribute in the index cluster to be verified, which is used for indicating the importance degree among the indexes, aiming at the index cluster to be verified, which is formed by each first index belonging to the same upper index in each level; wherein the test evaluation result is determined based on a preset first evaluation standard;
The generation module generates an interval judgment matrix according to the test evaluation result; for each target attribute, the interval judgment matrix comprises a lower importance limit value and an upper importance limit value of the target attribute of each first index relative to the target attribute of other first indexes;
the first determining module is used for determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the interval judgment matrix;
the third acquisition module is used for acquiring an interval evaluation result corresponding to each target attribute of each second index of the lowest level; wherein the interval evaluation result is determined based on a preset second evaluation standard;
the second determining module is used for determining an optimal value weight evaluation result of each target attribute of each first index based on the interval weight vector, the interval evaluation result, a preset target function and constraint conditions; wherein the objective function is maximally determined based on the comprehensive prospect value;
the second determination module is further configured to:
Determining a target reference point corresponding to each target attribute of each second index based on each interval evaluation result; wherein the target reference point comprises: a positive reference point and a negative reference point; the positive reference point and the negative reference point are determined based on an ideal point method and a gray correlation analysis method;
for n second indexes of the same layer in the spacecraft ground equivalence test, set up And for the kth interval evaluation result corresponding to the p second index, the comprehensive evaluation matrix corresponding to the K interval evaluation results of each second index is shown in the following formula:
According to the following formula, positive ideal points and negative ideal points are selected as positive reference points and negative reference points respectively by combining an ideal point method and a gray correlation analysis method:
；
determining, for each second index, a benefit value of each section evaluation result of each target attribute relative to a negative reference point and a loss value relative to a positive reference point under the second index according to the following formula based on a target reference point and a plurality of section evaluation results corresponding to each target attribute of the second index;
；；
In the method, in the process of the invention, Representing the evaluation result of the jth interval under the ith indexA benefit value relative to a negative reference point; representing the evaluation result of the jth interval under the ith index Loss value relative to positive reference point; the loss valueAnd the benefit valueCalculating the relative position relation between the target reference point and the interval evaluation value;
Is provided with The p index of the target reference point is the k interval evaluation result corresponding to the p second index isThe calculation method of the loss value and the gain value of the target reference point and the interval evaluation value under different position relations is as follows:
When (when) At the time of cost, the benefit value isThe loss value is 0; or benefit, benefit value 0, loss value；
When (when)At the time of cost, the profit value is 0, and the loss value is; Or benefit value of; The loss value is 0;
When (when) At the time of cost, the benefit value isThe loss value is 0; or benefit, benefit value is 0, loss value is；
When (when)At the time of cost, the profit value is 0, and the loss value is; Or benefit value ofThe loss value is 0;
When (when) At the time of cost, the benefit value isLoss value of; Or benefit value ofLoss value of；
When (when)When the cost type is adopted, the profit value is 0, and the loss value is 0; benefit, benefit value is 0, loss value is 0;
Determining an optimal value weight evaluation result of each target attribute of each first index through a preset objective function and constraint conditions based on the interval weight vector and the loss value and the gain value corresponding to each target attribute of each second index;
The index weight search model corresponding to the objective function is as follows:
；
wherein V is the comprehensive prospect value of the j interval evaluation results; 、 Respectively represent the ith index weight Decision weights of the corresponding positive and negative foreground values;、 representing risk attitudes in the face of returns and losses, respectively; c is a first coefficient; d is a second coefficient; And Respectively represent the ith index weightUpper-normalized feature vectors and lower-normalized feature vectors of (a).
5. The apparatus of claim 4, wherein the first determining module is further configured to:
if the interval judgment matrix of each target attribute in the index cluster to be verified meets a preset consistency condition, decomposing each interval judgment matrix into an upper limit decomposition matrix and a lower limit decomposition matrix;
Determining an interval weight vector corresponding to each target attribute in the index cluster to be verified based on the upper limit decomposition matrix and the lower limit decomposition matrix corresponding to each interval judgment matrix; for each target attribute, the interval weight vector includes a weight upper limit value and a weight lower limit value corresponding to the target attribute of each first index.
6. The apparatus of claim 4, wherein the target attribute comprises: test completion and/or test confidence.
7. An electronic device comprising a processor and a memory, the memory storing machine executable instructions executable by the processor, the processor executing the machine executable instructions to implement the method of index weight assessment for spacecraft ground equivalent testing of any of claims 1-3.
8. A machine-readable storage medium storing machine-executable instructions that, when invoked and executed by a processor, cause the processor to implement the method for index weight assessment of spacecraft ground equivalent test of any one of claims 1-3.
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