Civil aviation unit event investigation system efficiency evaluation method and system

Abstract

The invention discloses a civil aviation unit event investigation system efficiency evaluation method and system. The method comprises the following steps: S1, constructing an evaluation index system and historical sample evaluation data; s2, inputting the normalized historical sample evaluation data into an index weight assignment model, and obtaining the weight corresponding to each index by the index weight assignment model through P calculation modules; s3, constructing a topological network by taking the indexes as network nodes, and correcting the weight of the fusion indexes through the topological network; and S4, evaluating based on the evaluation index system to obtain evaluation data of each index, and calculating to obtain an efficiency evaluation result. According to the invention, each calculation module of the index weight assignment model obtains the weight corresponding to each index, an improved topology potential is obtained through topology network construction, and the weight of each index is corrected and fused, so that a single index evaluation result and a total efficiency evaluation result of a civil aviation unit are obtained. Performance evaluation of a civil aviation unit and efficiency evaluation management of a civil aviation management unit are realized.

Description

Technical Field

[0001] The present invention relates to the field of civil aviation unit event investigation and evaluation, and in particular to a civil aviation unit event investigation system effectiveness evaluation method and system. Background Art

[0002] In order to strengthen the construction of the incident investigation system of civil aviation units (mainly civil aviation production and operation units), the Civil Aviation Administration of China issued and implemented the "Guidelines for the Construction of Aircraft Incident Investigation System for Civil Aviation Production and Operation Units" (Civil Aviation General Security No.

[2020] 5) in 2020, prompting civil aviation units to continuously improve and enhance incident investigations, civil aircraft design and manufacturing improvements, etc. Incident investigation of civil aviation units is an important task, a complex and systematic work involving multiple departments and multiple personnel. Civil aviation management units need to effectively evaluate the system effectiveness of different civil aviation units. However, since the incident investigation system involves many sections and projects, generally including investigation organizations or institutions, emergency response investigation work manuals, investigator teams, investigation equipment or equipment, engineering test analysis, safety recommendation management, etc., these sections and projects each include subordinate specific projects. The incident investigation system is constructed in sequence according to the subordinate levels. How to evaluate the system effectiveness is a major problem for management departments to exercise management and supervision. When conducting performance evaluation of civil aviation units, weak links can be effectively discovered, shortcomings can be made up, incident investigation work can be continuously consolidated and deepened, the system maturity can be improved, efforts can be made to build a more scientific, reasonable, and safety-focused investigation system, and the actual role of investigation in promoting safety can be better played. The incident investigation system is an important support for civil aviation safety, and it is also an important task for civil aviation units and civil aviation management units. How to conduct performance evaluation of civil aviation unit incident investigations is an important basis for promoting incident investigations, and it is also a current difficulty and key task, and evaluation research is urgently needed. Summary of the invention

[0003] The purpose of the present invention is to solve the technical problems pointed out by the background technology, and to provide a method and system for evaluating the effectiveness of the incident investigation system of a civil aviation unit. Each calculation module of the indicator weight assignment model processes the historical sample evaluation data according to different methods to obtain the weights corresponding to each indicator. Then, a topological network is constructed according to the present invention, and the comprehensive attributes of each indicator are calculated by taking the indicator as the network node. The comprehensive attributes are obtained by fusion calculation of the weights of the same indicator in the indicator weight assignment model. The improved topological potential is obtained based on the topological network construction and the weights of each indicator are obtained by correction fusion. Then, the indicator evaluation results corresponding to each indicator are obtained, and all indicator evaluation results are added together to obtain the final performance evaluation result.

[0004] The purpose of the present invention is achieved through the following technical solutions:

[0005] A method for evaluating the effectiveness of an incident investigation system of a civil aviation unit, the method comprising:

[0006] S1. Construct an evaluation index system including an index item library, which includes several upper and lower level index items and corresponding evaluation criteria; construct historical sample evaluation data, which is obtained by sequentially evaluating the index items based on the evaluation index system, and perform data normalization on the historical sample evaluation data;

[0007] S2. Construct an indicator weight assignment model, input the normalized historical sample evaluation data into the indicator weight assignment model, the indicator weight assignment model includes P calculation modules, each calculation module obtains the weight corresponding to each indicator;

[0008] S3. Use the indicators as network nodes to construct a topological network. The improved topological potential expression of the topological network is as follows: d ij represents the comprehensive attribute difference between indicators i and j, δ represents the control coefficient, Q j Represents the comprehensive attribute of index j, and the expression is as follows: p represents the pth calculation module in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, C j represents the amount of information contained in index j, x′ pj Represents the data of the attribute value corresponding to the pth calculation module and the index j after dimensionless processing; the weight of the index j after the topological network correction is obtained according to the following formula

[0009] S4: Based on the evaluation index system, the evaluation data of each indicator is obtained, and the evaluation data of each indicator is normalized and combined with the weight obtained in step S3. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

[0010] In order to better implement the present invention, in step S4, the evaluation data of each indicator also includes the following data updating processing method before normalization processing: calculating the mission completion ratio of the indicator Where P a represents the actual evaluation data of the indicator, P m Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to Otherwise no processing is done.

[0011] The present invention provides a preferred indicator weight assignment model technical solution as follows: the indicator weight assignment model includes a hierarchy analysis calculation module, a priority diagram calculation module, an entropy weight calculation module, and a coefficient of variation calculation module. The hierarchy analysis calculation module uses the hierarchy analysis method to perform pairwise comparisons with indicators as factors.

[0012] Compare and get the judgment matrix A and find its maximum eigenvalue λ max and normalized eigenvectors, and obtain the weights A1 corresponding to each indicator after consistency test; the priority diagram calculation module uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the importance ratio of a certain indicator as the weight A2; the entropy weight calculation module uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator; the coefficient of variation method calculation module uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator.

[0013] Preferably, the judgment matrix A in the hierarchical analysis calculation module is expressed as follows:

[0014] where a ij Indicates that index i corresponds to element x i The element x corresponding to index j j The impact ratio.

[0015] Preferably, the importance matrix expression in the priority diagram calculation module is as follows: where b ij Represents the relative importance value between indicator i and indicator j; add the matrix B to get the total value T n :

[0016] The weight A2 formula of a certain indicator is as follows: Weight b i It represents the sum of the data in the row where indicator i is located in the importance matrix.

[0017] Preferably, the entropy weight method calculation module uses the entropy weight method to obtain the discriminant matrix P j : where x′ j It represents the dimensionless data of indicator j; the contribution of indicator j is E j The expression is as follows:

[0018] The weight A3 of indicator j is expressed as follows: Where D j =1-E j .

[0019] Preferably, the coefficient of variation method calculation module uses the coefficient of variation method to obtain the coefficient of variation expression of the indicator j as follows: in represents the normalized mean of index j, S j It represents the standard deviation of index j after normalization;

[0020] After normalizing the coefficients of variation of all indicators, the weight A4 expression corresponding to indicator j is obtained as follows:

[0021] Weight

[0022] Preferably, in step S3, the weight matrix expression of the improved topological potential of the network nodes is as follows:

[0023]

[0024] A civil aviation unit incident investigation system performance evaluation system, comprising an indicator weight assignment model, an evaluation indicator system, historical sample evaluation data, a topological network and an effectiveness evaluation module, wherein the evaluation indicator system is constructed according to an indicator item library, and the indicator item library comprises a number of upper and lower level indicator items and corresponding evaluation criteria; the historical sample evaluation data is obtained by sequentially evaluating the indicators based on the evaluation indicator system, and the historical sample evaluation data is subjected to data normalization processing; the indicator weight assignment model is used to receive the historical sample evaluation data after input normalization processing, and the indicator weight assignment model comprises P calculation modules, and each calculation module obtains the weight corresponding to each indicator respectively;

[0025] The topological network is constructed with indicators as network nodes, and the improved topological potential expression of the topological network is as follows: d ij represents the comprehensive attribute difference between indicators i and j, δ represents the control coefficient, Q j Represents the comprehensive attribute of index j, and the expression is as follows: p represents the pth calculation module in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, C j represents the amount of information contained in the index J, x′ pj It represents the data of the attribute value corresponding to the p-th calculation module and the index j after dimensionless processing; the weight of the index J after the topological network correction is obtained according to the following formula

[0026] The performance evaluation module obtains evaluation data of each indicator based on the evaluation index system, normalizes the evaluation data of each indicator and adds them to the weights. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

[0027] Preferably, the performance evaluation module obtains evaluation data of each indicator based on the evaluation indicator system and calculates the mission completion ratio of the indicator. Where P a represents the actual evaluation data of the indicator, P m Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to Otherwise, no processing is performed; the performance evaluation module normalizes the evaluation data of each indicator after the update and compares them with the weights. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

[0028] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0029] (1) The present invention constructs an evaluation index system to obtain historical sample evaluation data. Each calculation module of the index weight assignment model processes the historical sample evaluation data according to different methods to obtain the weights corresponding to each index. Then, a topological network is constructed according to the present invention. The comprehensive attributes of each index are calculated by taking the index as the network node. The comprehensive attributes are obtained by fusion calculation of the weights of the same index in the index weight assignment model. An improved topological potential is obtained based on the topological network construction, and the weights of each index are obtained by correction fusion. Then the indicator evaluation results corresponding to each indicator are obtained, and the final performance evaluation result can be obtained by adding up all the indicator evaluation results.

[0030] (2) The present invention can scientifically evaluate the effectiveness of the complex event investigation system, obtain the individual indicator evaluation results and the overall effectiveness evaluation results of the civil aviation unit, realize the self-effectiveness evaluation of the civil aviation unit and the effectiveness evaluation management of the civil aviation management unit, and promote the civil aviation unit to improve its investigation capabilities and safety management effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The figure is a flow chart of the performance evaluation method of the present invention. DETAILED DESCRIPTION

[0032] The present invention is further described in detail below in conjunction with embodiments:

[0033] Example

[0034] like Figure 1 As shown, a method for evaluating the effectiveness of an incident investigation system of a civil aviation unit comprises:

[0035] S1. Construct an evaluation index system including an index item library, which includes several upper and lower level index items and corresponding evaluation standards. In this embodiment, the contents that civil aviation units need to evaluate include six first-level items, including investigation organizations or institutions, emergency response investigation work manuals, investigator teams, investigation equipment or equipment, engineering test analysis, and safety recommendation management. Each first-level project includes several second-level projects. For example, the first-level project of the investigation organization or institution includes four second-level projects, including document manuals, organizational structure, departmental responsibilities, and investigation mechanisms. For example, the first-level project of the investigator team includes five second-level projects, including investigator training, selection and appointment, responsibilities and authority, investigator file and certificate management, and occupational health protection. Each second-level project includes several third-level projects. For example, the second-level project of the document manual includes three-level projects such as clarifying the responsibilities of each department in the investigation and the qualification requirements of the relevant personnel in the investigation. For example, the second-level project of selection and appointment includes three-level projects such as authorization of qualified investigators, the number of qualified investigators, and the professional coverage of the selected investigators to meet the requirements. Therefore, the indicators of the indicator library in the evaluation indicator system of the present invention are also extracted according to the content that the civil aviation unit needs to evaluate and constructed according to the corresponding level, and at the same time, the corresponding evaluation standards are constructed according to the level. The evaluation indicator system constructed in this embodiment has 6 first-level indicators and 28 second-level indicators respectively, and several third-level indicators.

[0036] Construct historical sample evaluation data, which is obtained by evaluating the historical sample evaluation data in sequence according to the evaluation index system (the historical sample evaluation data is evaluated according to the evaluation index system to obtain its corresponding evaluation value, which is generally a score, also known as the data obtained by the evaluation corresponding to the index, and the evaluation value of a certain index corresponds to the content of the corresponding level that the aircraft production and operation unit needs to evaluate), and perform data normalization on the historical sample evaluation data. In some embodiments, the data normalization processing formula of the historical sample evaluation data is as follows:

[0037] X nar Indicates that the indicator corresponds to the standardized data, X min Indicates the minimum data in the corresponding data of the indicator, X max It indicates the maximum data among the data corresponding to the indicator, and X indicates the data corresponding to the indicator.

[0038] S2. Construct an indicator weight assignment model, input the normalized historical sample evaluation data into the indicator weight assignment model, and the indicator weight assignment model includes P calculation modules, each of which obtains the weight corresponding to each indicator. In some embodiments, the indicator weight assignment model includes a hierarchy analysis calculation module, a priority diagram calculation module, an entropy weight calculation module, and a coefficient of variation calculation module, a total of four calculation modules (i.e., P=4). The hierarchy analysis calculation module uses the hierarchy analysis method to compare the indicators as factors to obtain the judgment matrix A and find its maximum eigenvalue λ max And the normalized eigenvector, the weight A1 corresponding to each indicator is obtained through consistency test.

[0039] In some embodiments, the judgment matrix A of the hierarchical analysis calculation module is expressed as follows:

[0040] where a ij Indicates that index i corresponds to element x i The element x corresponding to index j j Then find its maximum eigenvalue λ max and eigenvector W, based on the largest eigenvalue λ max A double test of the consistency index CI and the consistency ratio CR is performed. After the test is passed, the feature vector W is normalized, thereby obtaining the normalized feature vector corresponding to each index and using them as the weight A1 in turn.

[0041] In a further embodiment, the maximum eigenvalue maxλ of the judgment matrix A is calculated

[0042] Calculate the consistency index CI (Consistency Index)

[0043]

[0044] Check the following table to obtain the corresponding average random consistency index RI (Random Index), as shown in the following table:

[0045] Table 3 Average random consistency index values

[0046] Matrix order n 2 3 4 5 6 7 8 9 10 … RI value 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 …

[0047] Calculate the consistency ratio CR (Consistency Ratio)

[0048]

[0049] Make a consistency judgment: When CR < 0.1, the judgment matrix A has satisfactory consistency and the analysis result is accepted; on the contrary, when CR ≥ 0.1, the judgment matrix A does not have satisfactory consistency and needs to be modified.

[0050] The above steps result in a single-layer ranking, which is the weight vector of a group of elements to an element in the previous layer. The total hierarchical ranking is to calculate the relative importance weight of the lowest factor relative to the highest factor layer by layer from top to bottom along the recursive hierarchy structure, that is, the importance weight of all factors at a certain level relative to the highest level. The total ranking weight is to synthesize the weights under the single criteria from top to bottom.

[0051] Assume that the previous layer A contains A1, A2, ..., A m There are m factors in total, and the hierarchical weights are a1, a2, ..., a m , and its next layer B contains n factors B1, B2, ..., B n , about A j The hierarchical single sorting weights are b 1j , b 2j , ..., b rj . Use the weight synthesis method to find the total hierarchical ranking weights b1, b2, ..., b of each factor in layer B. n ,Right now The calculation method is as follows:

[0052] Table 4. Hierarchical total ranking weight synthesis method

[0053]

[0054]

[0055] The weight vector obtained by the total hierarchical sorting still needs to be checked for consistency to verify whether the result is satisfactory. Suppose the consistency index based on the jth factor of the k-1th layer is The average random consistency index is Then the comprehensive indicators of the kth layer are:

[0056]

[0057] If CR (k) <0.1, it is considered that the judgments above the kth level of the hierarchy have overall satisfactory consistency and the analysis results are accepted; on the contrary, if CR (k) When ≥0.1, it is considered that the judgments above the kth level of the hierarchy do not have overall satisfactory consistency, and the judgment matrix needs to be corrected. In practical applications, if the single-level sorting has been tested to have satisfactory consistency, there is no need to perform a satisfactory consistency test on the whole, because it is not only very difficult to consider the whole, but also very difficult to adjust the overall judgment matrix.

[0058] The priority diagram calculation module uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the importance ratio of a certain indicator as the weight A2. The importance matrix expression of the priority diagram calculation module is as follows: where b ij Represents the relative importance value between the indicator and the indicator j; add the matrix B to get the total value T n : The weight A2 formula of a certain indicator (a certain indicator calculated by the second calculation module, such as indicator i) is as follows: Weight b i It represents the sum of the data in the row where indicator i is located in the importance matrix.

[0059] The entropy weight calculation module uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator. The entropy weight calculation module uses the entropy weight method to obtain the discriminant matrix P j : where x′ j It represents the dimensionless data of indicator j; the contribution of indicator j is E j The expression is as follows:

[0060] The weight A3 of indicator j is expressed as follows: Where D j =1-E j ,,0<W j <1, and ∑W j =1.

[0061] The coefficient of variation calculation module uses the coefficient of variation method to find the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator. The coefficient of variation calculation module uses the coefficient of variation method to obtain the coefficient of variation expression of indicator j as follows: in represents the normalized mean of index j, S j It represents the standard deviation of index j after normalization;

[0062] After normalizing the coefficients of variation of all indicators, the weight A4 expression corresponding to indicator J is obtained as follows:

[0063] Weight

[0064] S3. Use the indicators as network nodes to construct a topological network. The improved topological potential expression of the topological network is as follows: d ij represents the comprehensive attribute difference between indicators i and j, δ represents the control coefficient (in this embodiment, the value is 1), Q j Represents the comprehensive attribute of index j, and the expression is as follows: p represents the pth calculation module in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, C j represents the amount of information contained in index j, x′ pj Represents the data of the attribute value corresponding to the pth calculation module and the index j after dimensionless processing; the weight of the index j after the topological network correction is obtained according to the following formula

[0065] In some embodiments, the weight matrix expression of the improved topological potential of the network nodes is as follows:

[0066]

[0067] This example takes the effectiveness evaluation of the incident investigation system of COMAC aircraft production and operation units as an example, and lists the weights of some indicators as follows:

[0068]

[0069] S4: Based on the evaluation index system, the evaluation data of each indicator is obtained, and the evaluation data of each indicator is normalized and combined with the weight obtained in step S3. Multiply the corresponding indicators and add up the multiplication results of all indicators to get the performance evaluation result. First, normalize the evaluation data of indicator j and the weight of indicator j. The result j is obtained by multiplying them together (the multiplication of the index of the present invention and the corresponding weight of the index constitutes the index evaluation result corresponding to the index), and the results j of all the indicators are added together to obtain the performance evaluation result.

[0070] In some embodiments, step S4 can be completely replaced by: obtaining evaluation data of each indicator based on the evaluation indicator system, and calculating the mission completion ratio of the indicator Where P a represents the actual evaluation data of the indicator, P m Indicates the expected evaluation data set by the indicator (that is, the expected target data set by the indicator, that is, the expected target achieved by the indicator); if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to Otherwise, no processing is performed. The evaluation data of each indicator after update is normalized and then compared with the weight obtained in step S3. Multiply the corresponding indicators and add up the multiplication results of all indicators to get the performance evaluation result. First, update the evaluation data after normalization of indicator j and the weight of indicator j The result j is obtained by multiplying (the multiplication of the index of the present invention and the corresponding weight of the index constitutes the index evaluation result corresponding to the index), and the results j of all the indicators are added to obtain the performance evaluation result. This embodiment takes the performance evaluation of the incident investigation system of the aircraft production and operation unit of COMAC as an example, and finally obtains the performance evaluation result of 93.3894. The incident investigation system of COMAC is evaluated using the invention method, and the performance evaluation method has been fully verified and tested. For the performance evaluation work in related fields, by establishing the performance evaluation method of the incident investigation system of aircraft production and operation units, the evaluation calculation results can scientifically reflect the maturity of the system construction and the actual performance, provide a basis for the evaluation of the system construction, and provide a reference for clarifying the direction of system improvement.

[0071] A performance evaluation system for the incident investigation system of a civil aviation unit includes an indicator weight assignment model, an evaluation indicator system, historical sample evaluation data, a topological network, and an effectiveness evaluation module. The evaluation indicator system is constructed according to an indicator item library, and the indicator item library contains several upper and lower level indicator items and corresponding evaluation standards; the historical sample evaluation data is obtained by sequentially evaluating the indicators based on the evaluation indicator system, and the historical sample evaluation data is normalized; the indicator weight assignment model is used to receive the input normalized historical sample evaluation data, and the indicator weight assignment model includes P calculation modules, each of which obtains the weight corresponding to each indicator. The topological network is constructed with indicators as network nodes, and the improved topological potential expression of the topological network is as follows: d ij represents the comprehensive attribute difference between indicators i and j, δ represents the control coefficient, Q j Represents the comprehensive attribute of index j, and the expression is as follows: p represents the pth calculation module in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, C j represents the amount of information contained in index j, x′ pj Represents the data of the attribute value corresponding to the pth calculation module and the index j after dimensionless processing; the weight of the index j after the topological network correction is obtained according to the following formula

[0072] The performance evaluation module obtains the evaluation data of each indicator based on the evaluation index system, normalizes the evaluation data of each indicator and adds them to the weights. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

[0073] In some embodiments, the performance evaluation module obtains evaluation data of each indicator based on the evaluation indicator system, and the performance evaluation module calculates the mission completion ratio of the indicator. Where P arepresents the actual evaluation data of the indicator, P m Indicates the expected evaluation data set by the indicator (that is, the expected target data set by the indicator, that is, the expected target achieved by the indicator); if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to Otherwise, no processing is done; the performance evaluation module normalizes the evaluation data of each indicator after update and adds them to the weights. Multiply the corresponding indicators and add up the multiplication results of all indicators to get the performance evaluation result (first update the evaluation data after normalization of indicator j and the weight of indicator j Multiply them to get the result j, and add the results j of all indicators to get the performance evaluation result).

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the effectiveness of an incident investigation system of a civil aviation unit, characterized by: The methods include: S1. Construct an evaluation index system including an index item library, which includes several upper and lower level index items and corresponding evaluation criteria; construct historical sample evaluation data, which is obtained by sequentially evaluating the index items based on the evaluation index system, and perform data normalization on the historical sample evaluation data; S2. Construct an indicator weight assignment model, input the normalized historical sample evaluation data into the indicator weight assignment model, the indicator weight assignment model includes P calculation modules, each calculation module obtains the weight corresponding to each indicator; S3. Use the indicators as network nodes to construct a topological network. The improved topological potential expression of the topological network is as follows: d ij represents the comprehensive attribute difference between indicators i and j, δ represents the control coefficient, Q j Represents the comprehensive attribute of index j, and the expression is as follows: p represents the pth calculation module in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, C j represents the amount of information contained in index j, x′ pj Represents the data of the attribute value corresponding to the pth calculation module and the index j after dimensionless processing; the weight of the index j after the topological network correction is obtained according to the following formula S4: Based on the evaluation index system, the evaluation data of each indicator is obtained, and the evaluation data of each indicator is normalized and combined with the weight obtained in step S3. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

2. The method for evaluating the effectiveness of the incident investigation system of a civil aviation unit according to claim 1, characterized in that: In step S4, the evaluation data of each indicator before normalization also includes the following data updating processing method: calculating the mission completion ratio of the indicator Where P a represents the actual evaluation data of the indicator, P m Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to Otherwise no processing is done.

3. The method for evaluating the effectiveness of the civil aviation unit incident investigation system according to claim 1 or 2, characterized in that: The index weight assignment model includes a hierarchical analysis calculation module, a priority diagram calculation module, an entropy weight calculation module, and a coefficient of variation calculation module. The hierarchical analysis calculation module uses the hierarchical analysis method to compare the indexes as factors to obtain the judgment matrix A and calculate its maximum eigenvalue λ. max And the normalized feature vector, the weight A1 corresponding to each indicator is obtained through consistency test; The priority diagram calculation module uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the importance ratio of a certain indicator as the weight A2; The entropy weight calculation module uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight corresponding to the indicator A3; The coefficient of variation method calculation module uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator.

4. The method for evaluating the effectiveness of the incident investigation system of a civil aviation unit according to claim 3, characterized in that: The judgment matrix A in the hierarchical analysis calculation module is expressed as follows: where a ij Indicates that index i corresponds to element x i The element x corresponding to index j j The impact ratio.

5. The method for evaluating the effectiveness of the incident investigation system of a civil aviation unit according to claim 3, characterized in that: The importance matrix expression in the priority diagram calculation module is as follows: where b ij Represents the relative importance value between indicator i and indicator j; add the matrix B to get the total value T n : The weight A2 formula of a certain indicator is as follows: b i It represents the sum of the data in the row where indicator i is located in the importance matrix.

6. The method for evaluating the effectiveness of the incident investigation system of a civil aviation unit according to claim 3, characterized in that: The entropy weight method calculation module uses the entropy weight method to obtain the discriminant matrix P j : where x′ j It represents the dimensionless data of indicator j; the contribution of indicator j is E j The expression is as follows: The weight A3 of indicator j is expressed as follows: Among them, D j =1-E j .

7. The method for evaluating the effectiveness of the incident investigation system of a civil aviation unit according to claim 3, characterized in that: The coefficient of variation method calculation module uses the coefficient of variation method to obtain the coefficient of variation expression of indicator j as follows: in represents the normalized mean of index j, S j It represents the standard deviation of index j after normalization; After normalizing the coefficients of variation of all indicators, the weight A4 expression corresponding to indicator j is obtained as follows:

8. The method for evaluating the effectiveness of the incident investigation system of a civil aviation unit according to claim 1, characterized in that: In step S3, the weight matrix expression of the improved topological potential of the network nodes is as follows:

9. A civil aviation unit incident investigation system effectiveness evaluation system, characterized by: It includes an indicator weight assignment model, an evaluation indicator system, historical sample evaluation data, a topological network and an efficiency evaluation module. The evaluation indicator system is constructed according to an indicator item library, and the indicator item library contains a number of upper and lower level indicator items and corresponding evaluation criteria; the historical sample evaluation data is obtained by sequentially evaluating the indicators based on the evaluation indicator system, and the historical sample evaluation data is normalized; the indicator weight assignment model is used to receive the historical sample evaluation data after input normalization, and the indicator weight assignment model includes P calculation modules, each of which obtains the weight corresponding to each indicator; The topological network is constructed with indicators as network nodes, and the improved topological potential expression of the topological network is as follows: d ij represents the comprehensive attribute difference between indicators i and j, δ represents the control coefficient, Q j Represents the comprehensive attribute of index j, and the expression is as follows: p represents the pth calculation module in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, C j represents the amount of information contained in index j, x′ pj Represents the data of the attribute value corresponding to the pth calculation module and the index j after dimensionless processing; the weight of the index j after the topological network correction is obtained according to the following formula The performance evaluation module obtains evaluation data of each indicator based on the evaluation index system, normalizes the evaluation data of each indicator and adds them to the weights. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

10. The civil aviation unit incident investigation system effectiveness evaluation system according to claim 9, characterized in that: The performance evaluation module obtains the evaluation data of each indicator based on the evaluation indicator system and calculates the mission completion ratio of the indicator. Where P a represents the actual evaluation data of the indicator, P m Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to Otherwise, no processing is performed; the performance evaluation module normalizes the evaluation data of each indicator after the update and compares them with the weights. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

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