Cross-domain information chain evaluation method and system based on analytic hierarchy process and medium

Abstract

The invention belongs to the field of system engineering, and discloses a cross-domain information chain evaluation method and system based on an analytic hierarchy process, and a medium. According to the method, the analytic hierarchy process is adopted, qualitative description and quantitative analysis are combined, the comprehensive evaluation result of the information chain can be efficiently and accurately given, and important support is provided for rapid optimization iteration of a cross-domain information chain construction scheme. Compared with an expert evaluation method, the method has a rigorous and clear calculation process and has higher interpretability. Compared with a simulation deduction method, computing resources and time cost are effectively reduced. In addition, the method has universality and expandability. In practical application, the evaluation standard system only needs to be adjusted, refined or deleted according to practical conditions, information chain evaluation requirements of different objects in different fields can be met, and the method has high engineering application value.

Description

Technical Field

[0001] The present invention relates to the field of system engineering, and in particular to a cross-domain information chain evaluation method, system and medium based on hierarchical analysis method. Background Art

[0002] In modern multi-domain collaborative operations, efficiently integrating resources distributed across different dimensions to build a complete and efficient information chain is a key technical challenge in achieving enhanced collaborative effectiveness. A typical multi-domain information chain involves situational awareness, communication transmission, navigation and positioning, command decision-making, and mission execution. These elements are numerous, widely distributed, and frequently interact with one another. By optimizing the construction and operation mechanisms of the information chain and achieving efficient collaboration across all links, overall operational effectiveness can be significantly improved.

[0003] Currently, there are two common evaluation methods for cross-domain information chains. The first is expert evaluation, which involves organizing experts to review information chain plans. While this method is simple to use, the evaluation results are susceptible to subjective factors and lack quantitative evidence. The second is simulation-based evaluation, which uses computer simulation technology to conduct simulation experiments based on digital models and conduct evaluations based on the simulation results. This method relies on the establishment of digital models and the accumulation of comprehensive basic data, and requires significant computing power and time.

[0004] Therefore, in response to the needs of multi-domain collaborative operations, it is urgent to establish a cross-domain information chain evaluation method to provide a reliable basis for the optimal design and efficiency improvement of the information chain. Summary of the Invention

[0005] In order to solve the technical defects of the existing technology such as strong subjectivity of expert evaluation and high cost of simulation deduction, and to achieve objective and efficient comprehensive evaluation of cross-domain information chains, this application provides a cross-domain information chain evaluation method, system and medium based on hierarchical analysis method.

[0006] First, a cross-domain information chain evaluation method based on the analytic hierarchy process is provided, which adopts the following technical solutions:

[0007] Construct the judgment matrix of each level of the cross-domain information chain evaluation standard system and obtain the importance weight of the evaluation factors at each level;

[0008] Quantify the lowest-level capability indicators of the cross-domain information chain evaluation standard system and obtain quantitative scores;

[0009] The comprehensive score of the cross-domain information chain is calculated based on the importance weights and quantitative scores of the evaluation factors in the cross-domain information chain evaluation standard system.

[0010] Furthermore, in the cross-domain information chain evaluation standard system, the first-level evaluation elements include: situational awareness capability, communication capability, command capability, collaborative execution capability and positioning and navigation capability.

[0011] Furthermore, the situational awareness capability includes concealment, comprehensiveness, accuracy and timeliness; and the communication capability includes concealment, timeliness, accuracy, comprehensiveness and security.

[0012] Furthermore, when constructing the judgment matrix of each level, the 1 to 9 scaling method is adopted, as follows:

[0013] Determine the n evaluation factors that need to be compared, recorded as , ,…, ,in is the i-th evaluation factor that needs to be compared, Is the jth evaluation factor to be compared, construct an n×n matrix, where the elements Indicates evaluation factors Relative to evaluation factors The importance of ; the matrix satisfies the diagonal elements ; .

[0014] Furthermore, when obtaining the importance weights of the evaluation factors in each level, the specific steps are as follows: performing eigenvalue decomposition on the judgment matrix and completing consistency check, normalizing the eigenvector corresponding to the maximum eigenvalue, and obtaining the importance weights of the evaluation factors.

[0015] Furthermore, when quantifying and scoring the lowest-level capability indicators, the details are as follows: using the indicator quantification method, a normalized score is given to each quantitative and qualitative indicator.

[0016] Furthermore, the method for calculating the comprehensive score of the cross-domain information chain is as follows:

[0017]

[0018] in, Represents the importance weight of the first-level evaluation factor; represents the score of the first-level evaluation factor; I is the number of first-level evaluation factors; Obtained through the weighted sum of the scores of the next level indicators.

[0019] In a second aspect, a cross-domain information chain evaluation system based on the analytic hierarchy process is provided, which is used to implement the cross-domain information chain evaluation method based on the analytic hierarchy process as described in the first aspect, and includes the following modules:

[0020] The information chain evaluation standard system construction module is used to build a hierarchical cross-domain information chain evaluation standard system;

[0021] The judgment matrix construction module is used to construct the judgment matrix of each level and obtain the importance weight of the evaluation factors in each level based on the hierarchical cross-domain information chain evaluation standard system;

[0022] The weight calculation module is used to perform eigenvalue decomposition on the judgment matrix, normalize the eigenvector corresponding to the maximum eigenvalue, and obtain the importance weight of the evaluation factor;

[0023] Data preprocessing module, used to quantify and score the lowest-level capability indicators;

[0024] The scoring module calculates the comprehensive score of the cross-domain information chain based on the importance weights of the evaluation factors and the quantitative scores.

[0025] In a third aspect, a computer-readable storage medium is provided, in which computer-executable instructions are stored. When the computer-executable instructions in the computer-readable storage medium are executed, the steps of the cross-domain information chain evaluation method based on the hierarchical analysis method as described in the first aspect are implemented.

[0026] The beneficial effects of the present invention are as follows:

[0027] This application adopts the hierarchical analysis method, which combines qualitative description and quantitative analysis. It can give comprehensive evaluation results efficiently and accurately, and provide important support for the rapid optimization and iteration of cross-domain information chain construction solutions. Compared with the expert evaluation method, this application has a rigorous and clear calculation process and higher interpretability. Compared with the simulation deduction method, it effectively reduces computing resources and time costs. In addition, this application is versatile and scalable. In practical applications, it is only necessary to adjust, refine or delete the evaluation standard system according to actual conditions to meet the information chain evaluation needs of different fields and different objects, and it has high engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a cross-domain information chain evaluation standard system;

[0029] Figure 2 It is a flow chart of the cross-domain information chain evaluation method based on the analytic hierarchy process;

[0030] Figure 3 This is the cross-domain information chain evaluation standard system of an embodiment of the present invention; DETAILED DESCRIPTION

[0031] The present invention will be further described below.

[0032] Assume that when a cluster of offshore operating platforms is conducting remote collaborative operations, it needs to implement task management through the control center and obtain information support provided by space-based observation systems and land-based systems to achieve multi-dimensional collaborative operations.

[0033] In terms of situational awareness, the detection equipment carried by offshore platforms is limited in range, with detection capabilities limited to targets within a range of 300-500 km. To expand monitoring coverage and establish an early warning system, it is necessary to integrate monitoring information provided by space-based observation systems and land-based systems.

[0034] In terms of communication transmission, information exchange between the offshore operation platform cluster and the control center and land-based system relies on ground-to-sea wireless communication links or satellite relay communications.

[0035] In terms of command and dispatch, after the offshore operation platform cluster receives instructions from the control center, the master control platform in the offshore operation platform cluster is responsible for coordinating the unified actions of each member platform.

[0036] In terms of collaborative execution, each member platform needs to decompose the instructions of the main control platform and collaborate to complete the work objectives.

[0037] In terms of positioning and navigation, the offshore operation platform cluster achieves its own positioning and navigation through satellite navigation receiving equipment, inertial navigation systems, navigation radars and other devices.

[0038] This paper uses the Analytic Hierarchy Process (AHP) to comprehensively evaluate the constructed cross-domain information chain evaluation standard system. The AHP (Analytical Hierarchy Process) is an evaluation method that combines traditional quantitative and qualitative analysis. Its basic concept is to decompose a complex problem into multiple hierarchical components based on interdependencies. The components within the same hierarchy are then compared and calculated to determine their relative importance and weights. A score for each level is then calculated using methods such as weighted sums or weighted products. The overall score for the entire evaluation standard system is then calculated from the bottom up.

[0039] According to the analysis of information chain closure requirements, the first-level evaluation elements of the cross-domain information chain evaluation standard system are composed of situational awareness capability, communication capability, command and dispatch capability, collaborative execution capability, and positioning and navigation capability. Figure 2 shown.

[0040] The evaluation indicators for situational awareness capabilities include concealment, comprehensiveness, accuracy, and timeliness. Concealment evaluation indicators are divided into electromagnetic radiation concealment and underwater acoustic radiation concealment. Electromagnetic radiation concealment includes electromagnetic radiation capability, electromagnetic radiation duration, electromagnetic radiation frequency, number of transit nodes, and electromagnetic radiation range. Underwater acoustic radiation concealment includes underwater acoustic radiation capability, underwater acoustic radiation duration, underwater acoustic radiation frequency, and number of transit nodes. Comprehensiveness evaluation indicators mainly refer to situational awareness range and situation grasp rate. Accuracy evaluation indicators mainly refer to situational awareness accuracy and recognition accuracy. Situational awareness accuracy includes position accuracy, velocity accuracy, and radiation source parameter analysis accuracy. Recognition accuracy includes type recognition accuracy, attribute recognition accuracy, and individual recognition accuracy. Timeliness evaluation indicators mainly refer to target navigation time and data update rate.

[0041] Evaluation indicators for communication capabilities include concealment, timeliness, accuracy, comprehensiveness, and security. Because both situational awareness and communication rely on electromagnetic wave propagation or underwater acoustic propagation, the communication capability concealment evaluation indicators are the same as the situational awareness concealment indicators, divided into electromagnetic radiation concealment and underwater acoustic radiation concealment. Timeliness evaluation indicators include communication latency, communication bandwidth, initial network access time, and non-initial network access time. Accuracy indicators mainly refer to bit error rate; comprehensiveness evaluation indicators mainly refer to communication range; and security evaluation indicators mainly refer to the communication system's identity authentication and access control capabilities, and illegal intrusion detection and disposal capabilities.

[0042] Evaluation indicators for command and dispatch capabilities include completeness, robustness, and timeliness. Completeness refers to the completeness of the command plan, robustness refers to the accuracy of impromptu command and control, and timeliness refers to the time it takes to create the plan.

[0043] Evaluation indicators for collaborative execution capabilities include completion, timeliness, and self-organizing capabilities. Completion refers to the completion rate of command and dispatch instructions, timeliness refers to the time it takes to execute instructions, and self-organizing capabilities refers to the success rate of collaborative execution of tasks between nodes.

[0044] Positioning and navigation capabilities are divided into relative positioning, absolute positioning, and navigation capabilities. These capabilities are evaluated by indicators such as concealment, timeliness, accuracy, and comprehensiveness. Concealment evaluation indicators primarily focus on electromagnetic radiation concealment, including electromagnetic radiation capacity, electromagnetic radiation duration, electromagnetic radiation frequency, number of transit nodes, and electromagnetic radiation range. Accuracy evaluation indicators primarily refer to positioning and navigation accuracy. Timeliness evaluation indicators primarily include single-position positioning time and data update rate. Comprehensiveness evaluation indicators primarily refer to the coverage of positioning and navigation capabilities.

[0045] This embodiment focuses on evaluating the support capabilities of land-based systems and space-based observation systems in the cross-domain information chain for the offshore operation platform cluster, and expands on the situational awareness capability and communication capability. Since the command capability, collaborative execution capability, and positioning and navigation capability are closely related to the capabilities of the offshore operation platform cluster itself, this example does not decompose the command capability, collaborative execution capability, and positioning and navigation capability, and sets their indicators as fixed values ​​as input to the comprehensive evaluation model. Therefore, the cross-domain information chain evaluation standard system adopted in this embodiment is as follows: Figure 3 As shown, it includes 5 first-level evaluation factors, namely situational awareness capability, communication capability, command and dispatch capability, collaborative execution capability and positioning and navigation capability; among them, the first-level evaluation factor of situational awareness capability includes 4 second-level evaluation factors, namely concealment, comprehensiveness, accuracy and timeliness; the first-level evaluation factor of communication capability includes 5 second-level evaluation factors, namely concealment, timeliness, accuracy, comprehensiveness and security.

[0046] Due to differences in the types of equipment used and their performance parameters, the overall effectiveness of cross-domain information chains can vary. This solution selects two different sets of situational awareness and communication equipment configurations to construct two closed-loop information chain solutions, as shown in Table 6. The evaluation method proposed in this paper is then used to perform a comprehensive scoring comparison of the two solutions.

[0047] This embodiment evaluates the constructed hierarchical cross-domain information chain evaluation standard system. The process of the cross-domain information chain comprehensive evaluation method based on the hierarchical analysis method is as follows: Figure 1 The specific steps are as follows:

[0048] Step 1: Construct the judgment matrix of each level of the cross-domain information chain evaluation standard system and obtain the importance weight of the evaluation factors at each level.

[0049] To measure the impact of different evaluation factors at different levels on the overall effectiveness of cross-domain information chains, it is necessary to gradually construct judgment matrices for each level in the cross-domain information chain evaluation standard system and calculate importance weights. For example, to measure the impact of situational awareness, communication, command and dispatch, collaborative execution, and positioning and navigation capabilities on the overall effectiveness of cross-domain information chains, the weights of each first-level evaluation factor in the comprehensive evaluation model must be calculated. A judgment matrix between the first-level evaluation factors must be constructed through pairwise comparisons. Similarly, to quantitatively describe the impact of second-level indicators such as concealment, comprehensiveness, accuracy, and timeliness on the evaluation of situational awareness, a judgment matrix between the elements at this level must also be calculated. The same applies to other indicators.

[0050] The judgment matrix in the hierarchical analysis method is defined as follows: Assume that there are n components at the same level , ,…, , the judgment matrix can be expressed as,

[0051]

[0052] in, Representation elements relatively the importance of In practical applications, It can be expressed using a scale of 1 to 9, and the specific meanings of each level of scale are shown in Table 1.

[0053] Table 1 1 to 9 scaling method

[0054]

[0055] For each level of judgment matrix, calculate the

[0056]

[0057] The maximum eigenvalue of and the corresponding eigenvector , where the superscript T represents the transpose of the matrix and the eigenvector is normalized.

[0058]

[0059] Normalized vector The element value in is the relative importance weight of the corresponding indicator item.

[0060] It should be noted that the judgment matrix may not meet the consistency requirements. In this case, the judgment matrix should be revised and improved before calculating the weights. The consistency of the judgment matrix can be determined by the consistency index and consistency ratio These two standards are used to test the consistency index The definition is as follows:

[0061]

[0062] in, is the maximum eigenvalue, is the order of the judgment matrix. The smaller the value, the higher the consistency.

[0063] Consistency ratio The definition is as follows:

[0064]

[0065]

[0066] in, is the average random consistency index, which is obtained by taking the arithmetic mean after repeatedly calculating the eigenvalues ​​of the random judgment matrix. The average random consistency index of the 2-8 dimensional matrix repeated 1000 times is shown in Table 2.

[0067] surface Average random consistency

[0068]

[0069] When the matrix consistency ratio When <0.1, the judgment matrix is ​​considered to have satisfactory consistency; otherwise, the judgment matrix needs to be adjusted to meet the consistency requirements.

[0070] In this implementation, we first construct a first-level evaluation factor judgment matrix to obtain the importance weight of each first-level evaluation factor:

[0071] like Figure 3 As shown in Table 3, the first-level evaluation factors include situational awareness capability, communication capability, command and dispatch capability, collaborative execution capability, and positioning and navigation capability. The relative importance of the elements is compared based on the 1-9 scale, as shown in Table 3.

[0072] Table 3 Pairwise comparison of primary evaluation factors in this embodiment

[0073]

[0074] The judgment matrix of the first-level evaluation factors constructed as follows:

[0075]

[0076] The consistency ratio of the matrix is ​​calculated according to the formula = 0.0716<0.1, meeting the consistency requirement.

[0077] Judgment Matrix Perform eigenvalue decomposition, normalize the eigenvector corresponding to the maximum eigenvalue, and obtain the importance weight of the first-level evaluation factor , where the superscript T represents the transpose of the matrix.

[0078]

[0079] Then construct the judgment matrix of the secondary evaluation factors and obtain the importance weight of each secondary evaluation factor:

[0080] The situational awareness capability evaluation consists of four evaluation elements: concealment, comprehensiveness, timeliness, and accuracy. The relative importance of the elements is compared based on the 1-9 scale, as shown in Table 4.

[0081] Table 4 Pairwise comparison of the secondary evaluation factors of situational awareness capability in this embodiment

[0082]

[0083] The judgment matrix of the secondary evaluation factors of situational awareness capability constructed as follows:

[0084]

[0085] The consistency ratio of the matrix is ​​calculated according to the formula =0.0854<0.1, which meets the consistency requirement. Perform eigenvalue decomposition, normalize the eigenvector corresponding to the maximum eigenvalue, and obtain the weights of each secondary evaluation factor of situational awareness capability , where the superscript T represents the transpose of the matrix.

[0086]

[0087] The communication capability evaluation consists of five evaluation factors: concealment, comprehensiveness, timeliness, accuracy, and security. The relative importance of the elements is compared based on the 1-9 scale, as shown in Table 5.

[0088] Table 5 Pairwise comparison of the secondary evaluation factors of communication capability in this embodiment

[0089]

[0090] The secondary evaluation factor judgment matrix of communication capability constructed as follows:

[0091]

[0092] The consistency ratio of the matrix is ​​calculated according to the formula =0<0.1, which meets the consistency requirement. Perform eigenvalue decomposition, normalize the eigenvector corresponding to the maximum eigenvalue, and obtain the weights of each secondary evaluation factor of communication capability , where the superscript T represents the transpose of the matrix.

[0093]

[0094] When constructing a judgment matrix, in addition to the 1-9 scaling method, there are many other scaling methods to choose from, such as the Delphi method, data statistics method, group decision-making method, etc.

[0095] Step 2: Quantify the lowest level capability indicators in the cross-domain information chain evaluation standard system

[0096] To quantitatively describe the comprehensive score of a cross-domain information chain, it is necessary to quantify and normalize the lowest-level capability indicators (qualitative or quantitative) in the evaluation standard system. This process converts indicators of different dimensions and dimensions into scores that can be uniformly weighted. The comprehensive score is then calculated layer by layer, working from bottom to top. Each indicator is scored in the range [0, 1]. Commonly used indicator quantification functions can be divided into the following two categories.

[0097] 1) The larger the indicator x, the higher the score The larger it is, the closer it is to 1. Commonly used quantization functions are:

[0098]

[0099]

[0100] in, Represents the original indicator value of the input, Indicates the upper threshold of the indicator. When , the score directly takes the maximum value 1; Represents the lower threshold of the indicator. When , the score directly takes the minimum value 0; when In the middle range When , the score is linearly mapped to . is a negative exponential function.

[0101] 2) The larger the indicator x, the higher the score The smaller it is, the closer it is to 0. Commonly used quantization functions are:

[0102]

[0103]

[0104] in, Represents the original indicator value of the input, Indicates the upper threshold of the indicator. When , the score directly takes the minimum value 0; Represents the lower threshold of the indicator. When , the score directly takes the maximum value 1; In the middle range When , the score is reversely mapped to . is a negative exponential function.

[0105] Assume that two cross-domain information chain closure schemes are constructed based on different devices: Scheme 1 and Scheme 2. A normalized score is given to each capability indicator using an indicator quantification method, with the value ranging from [0 to 1], as shown in Table 6.

[0106] Table 6 Cross-domain information chain closure solution

[0107]

[0108] Step 3: Calculate the comprehensive score of the cross-domain information chain based on the importance weights of the evaluation factors in the cross-domain information chain evaluation standard system and the quantitative scores.

[0109] Compare and calculate the elements at the same level to determine the relative importance ranking and weights, obtain the individual scores for each level through weighted sum or weighted product, and then calculate step by step from bottom to top to obtain the comprehensive score of the entire evaluation standard system.

[0110] After obtaining the quantitative scoring results of the lowest level, based on the calculation results of the relative importance weights of the elements at each level in step 1, the weighted sum method is used to calculate the comprehensive score of the cross-domain information chain step by step. .

[0111]

[0112] in, Represents the importance weight of the first-level evaluation factor; represents the score of the first-level evaluation factor (I is the number of first-level evaluation factors), Obtained through the weighted sum of the scores of the next level indicators, the calculation method is as follows:

[0113]

[0114] in, represents the score of the jth secondary evaluation factor under the i-th primary evaluation factor (J is the number of secondary evaluation factors); Represents the importance weight of the corresponding secondary evaluation factor.

[0115] In this embodiment, The scores are situational awareness capability, communication capability, command and dispatch capability, collaborative execution capability, and positioning and navigation capability. The individual capability score of the first-level evaluation factor is defined as the weighted sum of the scores of the subordinate second-level indicators.

[0116] Taking situational awareness as an example, They are the scores of concealment index, comprehensiveness index, accuracy index and timeliness index respectively. is the corresponding importance weight. The scores of other abilities are similar.

[0117] In this embodiment, the comprehensive score of the cross-domain information chain of Solution 1 is:

[0118] Situational awareness capabilities of Option 1 Rating

[0119]

[0120] in, is the weight of each secondary evaluation factor of situational awareness capability (obtained in step 1), It is a quantitative score after quantification and normalization of indicators related to situational awareness capabilities.

[0121] Communication ability score for

[0122]

[0123] in, is the weight of each secondary evaluation factor of communication capability (obtained in step 1), It is a quantitative score after quantification and normalization of indicators related to communication capabilities.

[0124] Comprehensive score of option 1 for

[0125]

[0126] in, is the weight of the first-level evaluation factor (obtained in step 1), represents the situational awareness capability score of scenario 1; Communication capability score of scenario 1; It represents the command and dispatch capability score of plan 1; It represents the collaborative execution capability score of plan 1; Indicates the positioning and navigation capability score of solution 1.

[0127] Calculate the comprehensive score of the cross-domain information chain of solution 2:

[0128] Situational Awareness Capabilities of Option 2 Rating

[0129]

[0130] in, is the weight of each secondary evaluation factor of situational awareness capability (obtained in step 1), It is a quantitative score after quantification and normalization of indicators related to situational awareness capabilities.

[0131] Communication ability score for

[0132]

[0133] in, is the weight of each secondary evaluation factor of communication capability (obtained in step 1), It is a quantitative score after quantification and normalization of indicators related to communication capabilities.

[0134] Comprehensive score of option 2 for

[0135]

[0136] in, is the weight of the first-level evaluation factor (obtained in step 1), represents the situational awareness capability score of scenario 1; Communication capability score of scenario 2; It represents the command and dispatch capability score of Scheme 2; It represents the collaborative execution ability score of plan 2; Indicates the positioning and navigation capability score of Scheme 2.

[0137] In summary, in the cross-domain information chain evaluation standard system constructed in this example, the situational awareness capability and communication capability of Option 2 are higher than those of Option 1. When the command and dispatch capability, collaborative execution capability, and positioning and navigation capability are the same, Option 2 has higher overall effectiveness.

[0138] The present invention also provides a cross-domain information chain evaluation system based on hierarchical analysis method, which includes the following modules:

[0139] The judgment matrix construction module is used to construct judgment matrices at each level based on the hierarchical cross-domain information chain evaluation and pricing system.

[0140] The weight calculation module is used to perform eigenvalue decomposition on the judgment matrix, normalize the eigenvector corresponding to the maximum eigenvalue, and obtain the importance weight of the evaluation factor.

[0141] The data preprocessing module is used to quantify the scores of the lowest-level capability indicators.

[0142] The scoring module calculates the comprehensive score of the cross-domain information chain based on the importance weights of the evaluation factors and the quantitative scores.

[0143] The present invention provides a computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium. When the computer-executable instructions in the computer-readable storage medium are executed, a cross-domain information chain evaluation method based on hierarchical analysis method is implemented.

[0144] Although the present invention has been disclosed above with reference to preferred embodiments, these embodiments are not intended to limit the present invention. Any equivalent changes or modifications made without departing from the spirit and scope of the present invention are also within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the content defined in the claims of this application.

Claims

1. A cross-domain information chain evaluation method based on hierarchical analysis method, characterized in that: The steps include: Construct the judgment matrix of each level of the cross-domain information chain evaluation standard system and obtain the importance weight of the evaluation factors at each level; Quantify the lowest-level capability indicators of the cross-domain information chain evaluation standard system and obtain quantitative scores; The comprehensive score of the cross-domain information chain is calculated based on the importance weights and quantitative scores of the evaluation factors in the cross-domain information chain evaluation standard system.

2. The cross-domain information chain evaluation method based on hierarchical analysis method according to claim 1 is characterized in that: In the cross-domain information chain evaluation standard system, the first-level evaluation elements include: situational awareness capability, communication capability, command capability, collaborative execution capability and positioning and navigation capability.

3. The cross-domain information chain evaluation method based on hierarchical analysis method according to claim 2 is characterized in that: The situational awareness capability includes concealment, comprehensiveness, accuracy and timeliness; the communication capability includes concealment, timeliness, accuracy, comprehensiveness and security.

4. The cross-domain information chain evaluation method based on hierarchical analysis method according to claim 1 is characterized in that: When constructing the judgment matrix at each level, the 1 to 9 scaling method is used, as follows: Determine the n evaluation factors that need to be compared, recorded as , ,…, ,in is the i-th evaluation factor that needs to be compared, Is the jth evaluation factor to be compared, construct an n×n matrix, where the elements Indicates evaluation factors Relative to evaluation factors The importance of ; the matrix satisfies the diagonal elements ; .

5. The cross-domain information chain evaluation method based on hierarchical analysis method according to claim 1 is characterized in that: When obtaining the importance weights of the evaluation factors at each level, the specific steps are as follows: perform eigenvalue decomposition on the judgment matrix and complete consistency check, normalize the eigenvector corresponding to the maximum eigenvalue, and obtain the importance weights of the evaluation factors.

6. The cross-domain information chain evaluation method based on hierarchical analysis method according to claim 1 is characterized in that: When quantifying and scoring the lowest-level capability indicators, the specific steps are as follows: Use the indicator quantification method to give normalized scores to each quantitative and qualitative indicator.

7. The cross-domain information chain evaluation method based on hierarchical analysis method according to claim 1 is characterized in that: The method for calculating the comprehensive score of the cross-domain information chain is as follows: in, Represents the importance weight of the first-level evaluation factor; represents the score of the first-level evaluation factor; I is the number of first-level evaluation factors; Obtained through the weighted sum of the scores of the next level indicators.

8. A cross-domain information chain evaluation system based on hierarchical analysis method, characterized in that: The method for implementing the cross-domain information chain evaluation method based on the hierarchical analysis method as claimed in claim 1 comprises the following modules: The information chain evaluation standard system construction module is used to build a hierarchical cross-domain information chain evaluation standard system; The judgment matrix construction module is used to construct the judgment matrix of each level and obtain the importance weight of the evaluation factors in each level based on the hierarchical cross-domain information chain evaluation standard system; The weight calculation module is used to perform eigenvalue decomposition on the judgment matrix, normalize the eigenvector corresponding to the maximum eigenvalue, and obtain the importance weight of the evaluation factor; Data preprocessing module, used to quantify and score the lowest-level capability indicators; The scoring module calculates the comprehensive score of the cross-domain information chain based on the importance weights of the evaluation factors and the quantitative scores.

9. A computer-readable storage medium storing computer-executable instructions, wherein when the computer-executable instructions in the computer-readable storage medium are executed, the method according to any one of claims 1 to 6 is implemented.

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