An aviation equipment task intelligent selection method based on AHP-EWM combined empowerment

Abstract

The present application relates to the technical field of aviation equipment integrated support and auxiliary decision-making, and particularly relates to an aviation equipment task intelligent selection method based on AHP-EWM combined weighting, comprising the following steps: constructing an aviation equipment task selection evaluation index system; based on the analytic hierarchy process (AHP), constructing a judgment matrix through the importance degree evaluation of each index, and calculating a subjective weight vector; obtaining the quantitative index original data of the aviation equipment to be evaluated, performing standardization processing, and calculating an objective weight vector of each index based on the entropy weight method (EWM); linearly weighting and combining the subjective weight vector and the objective weight vector to obtain a comprehensive weight vector of each index; multiplying the index data after standardization processing by the corresponding comprehensive weight and summing to obtain a comprehensive evaluation score, and outputting a task selection priority sequence according to the score. The present application takes into account efficiency, cost and risk, realizes global multi-objective optimal task selection, improves decision-making transparency, reduces the whole-life scheduling cost, and improves the human-machine collaborative support task success rate.

Description

Technical Field

[0001] This invention relates to the field of integrated support and auxiliary decision-making technology for aviation equipment, and in particular to an intelligent selection method for aviation equipment missions based on AHP-EWM combined weighting. Background Technology

[0002] The selection and evaluation of carrier-based aircraft missions is a crucial step in building aviation equipment maintenance and support capabilities and a vital decision-making tool for achieving aviation equipment maintenance and support objectives. To accelerate the development of carrier-based aircraft maintenance and support capabilities and ensure that aviation equipment maintenance and support operations are conducted in a well-ordered and effective manner during major operations such as military exercises and emergency operations, a scientific evaluation of carrier-based aircraft mission selection is essential.

[0003] Traditional shipboard aviation maintenance support departments primarily select mission aircraft based on the remaining lifespan of military aircraft, reliability, expected maintenance workload, and maintenance experience. This method is prone to problems such as tight aircraft resource scheduling and poor plan matching. Currently, commonly used multi-index evaluation methods include the Analytic Hierarchy Process (AHP), fuzzy evaluation method, principal component analysis (PCA), and entropy weight method. Among these, subjective evaluation methods (such as AHP) can reflect the evaluator's subjective judgment or intuition, but the results may be affected by the evaluator's lack of knowledge or experience. Objective evaluation methods (such as entropy weight method) use rigorous mathematical theory for comprehensive evaluation, but lack information on the evaluator's subjective judgment, which may lead to secondary indicators having a greater impact on the results than important indicators.

[0004] Therefore, there are certain limitations to using any one method alone. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent selection method for aviation equipment missions based on AHP-EWM combined weighting, thereby resolving the aforementioned problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for intelligent selection of aviation equipment missions based on AHP-EWM combined weighting, comprising the following steps: S1: Construct an evaluation index system for selecting aviation equipment missions. The index system includes four criterion layers: aircraft technical status, maintenance control, quality and safety, and system reliability, as well as multiple corresponding quantitative indicators. S2: Based on the Analytic Hierarchy Process (AHP), a judgment matrix is ​​constructed by experts assessing the importance of each indicator in the evaluation index system, and the subjective weight vector of each indicator is calculated. S3: Obtain the raw data of the quantitative indicators of the aviation equipment to be evaluated, perform standardization processing, and calculate the objective weight vector of each indicator based on the entropy weight method (EWM). S4: Based on the decision-maker's preference coefficient, the subjective weight vector and the objective weight vector are linearly weighted and combined to obtain the comprehensive weight vector of each indicator; S5: Multiply the standardized indicator data with the corresponding comprehensive weights and sum them to obtain the comprehensive evaluation score of each piece of aviation equipment. Sort the tasks according to the scores and output the priority sequence.

[0007] Preferably, the quantitative indicators in step S1 include: aircraft remaining life after overhaul, engine remaining life after overhaul, segment planned usage time utilization rate, aircraft scheduled maintenance nearing expiration rate, engine scheduled maintenance nearing expiration rate, parts nearing expiration rate, cycle work nearing expiration rate, aircraft failure rate, aircraft in-flight failure rate, aircraft mean time between failures, mission system failure rate, mission system in-flight failure rate, and mission system mean time between failures.

[0008] Preferably, step S2 further includes: constructing a judgment matrix for the criterion layer relative to the target layer and the index layer relative to the criterion layer using a 1-9 scaling method; and using the root method... , Calculate the largest eigenvalue of the judgment matrix. Use consistency indicators To verify and judge, the formula is as follows: Perform a consistency check. When the consistency ratio When the result is less than 0.1, the weight result is retained; the absolute subjective weight of each indicator is obtained by multiplying the weight of the criterion layer by the weight of the indicator layer.

[0009] Preferably, the standardization process in step S3 includes: applying a formula to positive indices. For negative indicators, the formula is used. And add the minimum translation α to eliminate zero values.

[0010] Preferably, the objective weight calculation in step S3 further includes: calculating the proportion of the i-th aviation equipment index value under the j-th index. ; Calculate the information entropy of the j-th indicator. ; Calculate objective weights based on information entropy .

[0011] Preferably, the formula for calculating the comprehensive weight in step S4 is as follows: ,in This is the decision-maker preference coefficient, with a value range of [0,1]. Subjective weighting, For objective weighting.

[0012] Preferably, the preference coefficient A value of 0.4 corresponds to a subjective weight of 40% and an objective weight of 60%.

[0013] Preferably, after step S1 and before step S3, the method further includes: using qualitative indicators such as "aircraft condition" and "whether failure to implement technical notification affects flight" to conduct a preliminary screening of the aviation equipment to be evaluated, and removing equipment that does not meet the requirements from the evaluation sequence.

[0014] Preferably, the "aircraft in good condition" includes four states: fully in good condition, in good condition, not in good condition, and in good condition but grounded. Equipment in the not in good condition or in good condition but grounded will be excluded.

[0015] The present invention also includes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method steps described above.

[0016] Compared with existing technologies, this invention organically combines subjective hierarchical analysis with objective entropy weighting, which not only makes full use of the experience and knowledge of domain experts, but also deeply explores the information value of objective data itself, avoiding the limitations of a single method. The objective weights are dynamically calculated based on the real-time data of the equipment to be evaluated, and can automatically adjust the importance of each indicator according to the actual changes in the status of the aircraft group, making the evaluation results more consistent with the current actual support situation. The complex multi-indicator comprehensive evaluation problem is transformed into intuitive numerical ranking results, providing commanders with scientific quantitative decision support for selecting mission aircraft, effectively improving the accuracy and efficiency of mission aircraft selection. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram of the structure of the computer device in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To further understand the content of this invention, a detailed description of the invention will be provided in conjunction with the accompanying drawings.

[0020] This application provides a method for intelligent selection of aviation equipment missions based on AHP-EWM combined weighting, including the following steps: S1: Construct an evaluation index system for selecting aviation equipment missions. The index system includes four criterion layers: aircraft technical status, maintenance control, quality and safety, and system reliability, as well as multiple corresponding quantitative indicators. S2: Based on the Analytic Hierarchy Process (AHP), a judgment matrix is ​​constructed by experts assessing the importance of each indicator in the evaluation index system, and the subjective weight vector of each indicator is calculated. S3: Obtain the raw data of the quantitative indicators of the aviation equipment to be evaluated, perform standardization processing, and calculate the objective weight vector of each indicator based on the entropy weight method (EWM). S4: Based on the decision-maker's preference coefficient, the subjective weight vector and the objective weight vector are linearly weighted and combined to obtain the comprehensive weight vector of each indicator; S5: Multiply the standardized indicator data with the corresponding comprehensive weights and sum them to obtain the comprehensive evaluation score of each piece of aviation equipment. Sort the tasks according to the scores and output the priority sequence.

[0021] This invention organically combines subjective hierarchical analysis with objective entropy weighting, making full use of the experience and knowledge of domain experts while deeply exploring the information value of objective data itself, thus avoiding the limitations of a single method. The objective weights are dynamically calculated based on real-time data of the equipment to be evaluated, and can automatically adjust the importance of each indicator according to changes in the actual status of the aircraft group, making the evaluation results more consistent with the current actual support situation. It transforms the complex multi-indicator comprehensive evaluation problem into intuitive numerical ranking results, providing commanders with scientific quantitative decision support for selecting mission aircraft, and effectively improving the accuracy and efficiency of mission aircraft selection.

[0022] Based on the above embodiments, the quantitative indicators in step S1 include: aircraft remaining life after overhaul, engine remaining life after overhaul, flight segment planned usage time utilization rate, aircraft scheduled maintenance nearing expiration rate, engine scheduled maintenance nearing expiration rate, parts nearing expiration rate, cycle work nearing expiration rate, aircraft failure rate, aircraft in-flight failure rate, aircraft mean time between failures, mission system failure rate, mission system in-flight failure rate, and mission system mean time between failures.

[0023] Based on the above embodiments, step S2 further includes: constructing the judgment matrix of the criterion layer relative to the target layer and the index layer relative to the criterion layer using the 1-9 scaling method; and using the root method. , Calculate the largest eigenvalue of the judgment matrix. Use consistency indicators To verify and judge, the formula is as follows: Perform a consistency check. When the consistency ratio When the result is less than 0.1, the weight result is retained; the absolute subjective weight of each indicator is obtained by multiplying the weight of the criterion layer by the weight of the indicator layer.

[0024] Based on the above embodiments, the standardization process in step S3 includes: applying a formula to positive indices. For negative indicators, the formula is used. And add the minimum translation α to eliminate zero values.

[0025] Based on the above embodiments, the objective weight calculation in step S3 further includes: calculating the proportion of the i-th aviation equipment index value under the j-th index. ; Calculate the information entropy of the j-th indicator. ; Calculate objective weights based on information entropy .

[0026] Based on the above embodiments, the formula for calculating the comprehensive weight in step S4 is as follows: ,in This is the decision-maker preference coefficient, with a value range of [0,1]. Subjective weighting, For objective weighting.

[0027] Based on this, the preference coefficient A value of 0.4 corresponds to a subjective weight of 40% and an objective weight of 60%.

[0028] Based on the above embodiments, after step S1 and before step S3, the following steps are also included: using qualitative indicators "aircraft condition" and "whether the lack of technical notification affects flight" to conduct a preliminary screening of the aviation equipment to be evaluated, and removing equipment that does not meet the requirements from the evaluation sequence.

[0029] Based on this, "aircraft condition" includes four states: fully operational, operational, not operational, and operational but grounded. Equipment in the not operational or operational but grounded states will be removed.

[0030] The following sections of the embodiments of the present invention will describe the embodiments of the electronic devices and computer storage media of the present invention. The embodiments of the electronic devices and computer storage media described below correspond to the method embodiments described above. Those skilled in the art can understand the implementation process described below based on the above description, and will not be described in detail here.

[0031] like Figure 2 The diagram shows the structure of a computer device provided in this application embodiment. A computer device 400 provided in this application embodiment includes: a memory 420, a processor 410, and a computer program stored in the memory 420 and executable on the processor 410. When the processor 410 executes the computer program, it implements the above-described method.

[0032] This application embodiment also provides a storage medium 430 on which a computer program is stored, and when the computer program is executed by the processor 410, it implements the above-described method.

[0033] The storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0034] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. "A plurality of" means two or more, unless otherwise explicitly specified.

[0035] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0036] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0037] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0038] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0039] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0040] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0041] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for intelligent selection of aviation equipment missions based on AHP-EWM combined weighting, characterized in that, Includes the following steps: S1: Construct an evaluation index system for selecting aviation equipment missions. The index system includes four criterion layers: aircraft technical status, maintenance control, quality and safety, and system reliability, as well as multiple corresponding quantitative indicators. S2: Based on the Analytic Hierarchy Process (AHP), a judgment matrix is ​​constructed by experts assessing the importance of each indicator in the evaluation index system, and the subjective weight vector of each indicator is calculated. S3: Obtain the raw data of the quantitative indicators of the aviation equipment to be evaluated, perform standardization processing, and calculate the objective weight vector of each indicator based on the entropy weight method (EWM). S4: Based on the decision-maker's preference coefficient, the subjective weight vector and the objective weight vector are linearly weighted and combined to obtain the comprehensive weight vector of each indicator; S5: Multiply the standardized indicator data with the corresponding comprehensive weights and sum them to obtain the comprehensive evaluation score of each piece of aviation equipment. Sort the tasks according to the scores and output the priority sequence.

2. The method according to claim 1, characterized in that, The quantitative indicators in step S1 include: remaining life after aircraft overhaul, remaining life after engine overhaul, segment planned usage time utilization rate, near-expiration rate of aircraft scheduled maintenance, near-expiration rate of engine scheduled maintenance, near-expiration rate of spare parts, near-expiration rate of cycle work, aircraft failure rate, aircraft in-flight failure rate, aircraft mean time between failures, mission system failure rate, mission system in-flight failure rate, and mission system mean time between failures.

3. The method according to claim 1, characterized in that, Step S2 further includes: The judgment matrices of the criterion layer relative to the target layer and the index layer relative to the criterion layer are constructed using a 1-9 scale method; the root method is then employed. ; Calculate the largest eigenvalue of the judgment matrix Use consistency indicators To verify and judge, the formula is as follows: Perform a consistency check. When the consistency ratio When the result is less than 0.1, the weight result is retained; the absolute subjective weight of each indicator is obtained by multiplying the weight of the criterion layer by the weight of the indicator layer.

4. The method according to claim 1, characterized in that, The standardization process in step S3 includes: applying a formula to positive indicators. For negative indicators, use the formula. And add the minimum translation α to eliminate zero values.

5. The method according to claim 1, characterized in that, The objective weight calculation in step S3 further includes: calculating the proportion of the i-th aviation equipment index value under the j-th index. ; Calculate the information entropy of the j-th indicator. ; Calculate objective weights based on information entropy .

6. The method according to claim 1, characterized in that, The formula for calculating the comprehensive weight in step S4 is as follows: ;in This is the decision-maker preference coefficient, with a value range of [0,1]. Subjective weighting, For objective weighting.

7. The method according to claim 6, characterized in that, The preference coefficient A value of 0.4 corresponds to a subjective weight of 40% and an objective weight of 60%.

8. The method according to claim 1, characterized in that, The process after step S1 and before step S3 includes: using qualitative indicators such as "aircraft condition" and "whether the lack of technical notification affects flight" to conduct a preliminary screening of the aviation equipment to be evaluated, and removing equipment that does not meet the requirements from the evaluation sequence.

9. The method according to claim 8, characterized in that, The "aircraft in good condition" includes four states: fully in good condition, in good condition, not in good condition, and in good condition but grounded. Equipment in the not in good condition or in good condition but grounded will be removed.

10. A computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the steps of the method as claimed in any one of claims 1 to 9.

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