32 results about "Intuitionistic fuzzy" patented technology

The invention discloses an infrared and visible light image multi-level fusion method and device based on fractional differential and an intuitive fuzzy set, and relates to the field of computer vision. The method comprises the following steps: respectively decomposing an infrared image and a visible light image based on an MDLatLRR decomposition method to obtain a corresponding basic component and a series of multi-scale detail components; fusing the detail components by using a rule based on an intuitionistic fuzzy set to obtain a detail fusion component; fusing the basic components by adopting a fractional order differential rule to obtain a basic fusion component; and obtaining a reconstructed image of the target object according to the detail fusion component and the basic fusion component. According to the method, the local texture richness is enhanced and the key feature extraction effect is improved through the rule of an intuitionistic fuzzy set, meanwhile, the overall feature of the image is effectively reserved through the global and memory features of fractional differential, and finally, the high-quality fusion effect is achieved through recombination of a detail fusion component and a basic fusion component.

The invention belongs to the technical field of cloud computing networks, and discloses a computing power network workload spatio-temporal dynamic prediction method and device, equipment and a medium, and the method comprises the steps: determining a fuzzy set for identifying a workload mode through employing a clustering algorithm based on dynamic time warping according to a performance index during operation; determining a state transition conditional probability matrix of the computing power node, the heterogeneous hypergraph and the working load mode; adopting hypergraph convolution kernel learning to obtain a heterogeneous feature fusion model of workload and computing power nodes; processing the fuzzy set by adopting a fuzzy membership covariance, and further training by adopting a time convolution network of a dynamic receptive field to obtain a time sequence feature of a workload; and according to the heterogeneous feature fusion model and the time sequence features of the workload, carrying out space-time fusion training of cross entropy measurement probability and fuzzy uncertainty by adopting a probability intuitionistic fuzzy relation matrix to obtain a workload space-time dynamic prediction model. The method has the beneficial effect that the error rate of resource scheduling decision is reduced.

This invention provides a parameter-driven, intuitionistic fuzzy logic method for evaluating the suitability of mega-span cavern sites, relating to the field of geotechnical engineering evaluation. This invention, for the first time, constructs a dedicated tunneling design index system for mega-span caverns integrating "rock mass quality, environmental response, shape effect, and support status." It separates evaluation criteria indicators from engineering response indicators, establishing a mapping relationship between the two through numerical simulation, making the evaluation process more consistent with engineering cognitive principles. Intuitionistic fuzzy numbers are used to quantify the merits of evaluation index values, achieving an organic fusion of objective data and fuzzy expression. The final output is a single, quantifiable site suitability index, enabling intuitive comparison of multiple sites and multiple indicators, greatly facilitating engineering decision-making. By replacing expert scoring with a pre-set mapping function, subjective interference is completely eliminated, ensuring that the evaluation results are entirely determined by the input parameters. Different personnel can obtain consistent conclusions, greatly improving the repeatability and engineering applicability of the method.

This invention discloses a method, storage medium, and device for aquaculture water quality assessment based on intuitionistic fuzzy set distance measures. The method includes: constructing an expert comment set based on water quality datasets collected under aquaculture conditions, and converting the expert comment set into an intuitionistic fuzzy matrix for aquaculture water quality assessment; constructing a Gaussian kernel-based dynamic hesitancy assignment model based on the intuitionistic fuzzy matrix to determine the hesitancy assignment of intuitionistic fuzzy numbers; forming quadruples of the intuitionistic fuzzy numbers and their corresponding hesitancy assignments in the intuitionistic fuzzy matrix; and calculating the intuitionistic fuzzy set distance measures with the optimal and worst water quality based on the quadruples of the intuitionistic fuzzy numbers to assess the aquaculture water quality. This invention can significantly improve the accuracy of aquaculture water quality assessment and enhance the timeliness and effectiveness of aquaculture water quality early warning.

The invention discloses a helmet lock remote control method and system based on the Internet, and relates to the technical field of Internet of Things control and intelligent decision, and the method comprises the steps: achieving the construction of multi-dimensional risk features of a user state through the combination of a context information tuple and a cloud agent cooperation mechanism and intuitive fuzzy modeling; the sensitivity of the system to user behavior differences is improved, unification of risk dynamic assessment and probability prediction is achieved through combination of an L1 kernel estimation function and an intuitionistic fuzzy entropy weight calculation mechanism, the generalization performance of the model is improved, and through combination of a grey correlation analysis model and improved intuitionistic fuzzy distance measurement, the accuracy of the system is improved. According to the method, multi-dimensional similarity calculation and risk grade division among user states are realized, the relativity of risk judgment is achieved, a continuous function optimization method of triangular fuzzy weighted geometric averaging is combined with a credibility driven fusion mechanism, a dynamic fusion decision of risk probability and similarity information is realized, and the reliability of risk judgment is improved. And the decision stability of the system in a complex scene is improved.

This invention discloses a multi-dimensional monitoring system and method for engineering project progress based on information technology, applicable to the monitoring field. The system includes: an initial construction plan construction module, a data acquisition and environmental monitoring module, a data analysis and plan optimization module, a construction progress prediction module, and a risk management module. By collecting multi-dimensional data from the construction site in real time and applying an intuitionistic fuzzy inference algorithm, this invention can dynamically adjust the construction plan to cope with constantly changing site conditions and external environmental factors. Utilizing the intuitionistic fuzzy inference algorithm to analyze the needs and bottlenecks of the construction project, combined with construction logic and physical constraints, allows for more precise resource allocation. A fuzzy logic controller handles fuzzy and uncertain situations, ensuring the project complies with all relevant building and safety standards. Through continuous monitoring and timely adjustments, project quality and safety are guaranteed.

The application provides a control method and device for a power converter of an energy storage system, a coupling relationship between active power and reactive power is analyzed through a power outer loop control model based on a virtual synchronous machine and a power coupling coefficient matrix, PI parameters of a reactive voltage compensation channel are adjusted based on the coupling relationship and a fundamental component extracted, a voltage reference value output by a PI controller after correction is obtained, a current value in a prediction time domain is predicted through a model-free predictive control method based on a bias format dynamic linearization in a current inner loop, and the voltage reference value and the current value are optimized in combination with an intuitionistic fuzzy model and a rough decision model, so that a target voltage reference value and a target current value generated after optimization are used for regulation and control. Therefore, through fusion of power decoupling, model-free predictive control, fundamental component extraction, and the intuitionistic fuzzy model and the rough decision model, adaptability, robustness and power quality of the power converter in a complex power grid environment are improved.

This invention discloses a method, equipment, and storage medium for selecting favorable areas of low-permeability carbonate gas reservoirs based on intuitionistic fuzzy multi-attribute boundary approximation region comparison (MABAC). Specifically, it includes the following steps: S1, screening key indicators of carbonate gas reservoirs for favorable area selection; S2, determining attribute weights based on the Brown-Warshall Method (BWM); S3, establishing a favorable area selection model for low-permeability carbonate gas reservoirs using the intuitionistic fuzzy multi-attribute boundary approximation region comparison method (MABAC); S4, calculating conditional probabilities, and then ranking the decision objectives included in the positive, boundary, and negative domains to obtain the favorable area selection results. This invention can simultaneously consider the influence of multiple factors on different schemes and grasp the priority relationship between factors.

The invention belongs to the technical field of power anomaly detection, and particularly relates to a power Internet of Things anomaly detection method and system based on granular ball intuitionistic fuzzy modeling, and the method comprises the steps: constructing a plurality of training granular ball intuitionistic fuzzy models corresponding to known category labels according to known normal data and abnormal data, and forming a training granular ball intuitionistic fuzzy set; constructing a plurality of to-be-detected granular ball intuitionistic fuzzy model sets of unknown categories by taking the training granular ball intuitionistic fuzzy set as a reference; calculating the fuzzy distance between each to-be-tested granular ball intuitionistic fuzzy model and all training granular ball intuitionistic fuzzy models; endowing a known category label corresponding to the training particle ball intuitionistic fuzzy model with the minimum fuzzy distance with corresponding unknown category data; judging whether the known category label endowed by the unknown category data is an abnormal label or not; and if yes, determining that the unknown category data is abnormal data, and generating structured alarm information. According to the method, the detection precision is remarkably improved, the calculation efficiency is high, and high interpretability is achieved.

The application discloses a cross-border network anomaly detection method based on intuitionistic fuzzy set and double-path learning, and belongs to the technical field of network security. The application aims at the problems of unstable feature form and poor cross-domain generalization ability caused by ignoring cognitive uncertainty in the existing method, proposes an IRU uncertainty evaluation paradigm, decomposes feature evaluation into three dimensions of evidence strength, mixed degree and form stability, and maps them to the intuitionistic fuzzy set domain; designs a risk-averse robust credibility score RTS to screen credible elite features; and constructs a double-path fidelity training architecture, which constrains the model decision logic to be anchored on the credible features through a fidelity loss function. The application realizes the synchronous improvement of detection performance and feature selection stability on multiple cross-border intrusion data sets, is especially suitable for cross-border network environments with strong resistance and significant distribution offset, and has the ability of rapid cold start deployment.

The application relates to a mobile phone product recommendation method based on comparison of question and answer text and comparison of video, a first comprehensive intuitionistic fuzzy number of a comparison question corresponding to an attribute is obtained based on a first emotion scoring agent; a mean value of the first comprehensive intuitionistic fuzzy numbers of all comparison questions corresponding to the attribute is calculated to obtain a first fuzzy number of a mobile phone product under the corresponding attribute; complete video content of an evaluation comparison video corresponding to the mobile phone product is obtained, and video text information of the complete video content is extracted; the video text information is split into multiple text parts according to the attribute, a second comprehensive intuitionistic fuzzy number of a text part corresponding to the attribute is obtained based on a second emotion scoring agent; the second comprehensive intuitionistic fuzzy numbers of all text parts corresponding to the attribute are aggregated to obtain a second fuzzy number of the mobile phone product under the corresponding attribute; a recommendation score of the mobile phone product is calculated based on the first fuzzy numbers and the second fuzzy numbers under all attributes, and a mobile phone product with the highest recommendation score is taken as a recommended product.

The invention discloses a ground wire state evaluation method and system based on an improved network hierarchy method, and aims at solving the problems that in a traditional evaluation method, indexes are numerous, data are disordered, and expert decision ambiguity is ignored. According to the system, key indexes are selected by constructing a ground wire original parameter system and combining industrial standards; key evaluation indexes are extracted by using a PCA dimension reduction technology, and data redundancy is reduced; an intuitive fuzzy number improved network analytic hierarchy process (ANP) is introduced, and a scientific and reasonable evaluation model is constructed. The system can accurately evaluate the state of the ground wire, provides a scientific basis for the operation and maintenance decision of a power system, and improves the evaluation efficiency and accuracy.

This invention belongs to the field of power anomaly detection technology, specifically relating to a power Internet of Things (IoT) anomaly detection method and system based on granular-sphere intuitionistic fuzzy modeling. The method includes: constructing multiple training granular-sphere intuitionistic fuzzy models with corresponding known category labels based on known normal and abnormal data, forming a training granular-sphere intuitionistic fuzzy set; constructing multiple sets of test granular-sphere intuitionistic fuzzy models with unknown categories using the training granular-sphere intuitionistic fuzzy set as a reference; calculating the fuzzy distance between each test granular-sphere intuitionistic fuzzy model and all training granular-sphere intuitionistic fuzzy models; assigning the known category label corresponding to the training granular-sphere intuitionistic fuzzy model with the smallest fuzzy distance to the corresponding unknown category data; determining whether the known category label assigned to the unknown category data is an anomaly label; if so, determining the unknown category data as anomaly data and generating structured alarm information. This invention significantly improves detection accuracy, has high computational efficiency, and possesses strong interpretability.

The invention relates to the related field of multispectral detection and multi-attribute decision, discloses a cotton foreign fiber optimal detection wave band optimization method based on an interval intuitionistic fuzzy set and a fusion weighting method, and aims to solve the problems that a traditional wave band division method is single in index and does not consider the correlation degree between different indexes and the like. The system comprises a data processing module M1 used for collecting and preprocessing foreign fiber spectrum data; the information feature module M2 is used for spectral information feature construction based on the preprocessed data; the multi-attribute decision-making module M3 is used for establishing a decision-making mechanism of the optimal detection wave band of the spectral data; and the result analysis module M4 is used for sensitivity analysis and method comparison. According to the method, the separability, the correlation and the information amount of the foreign fiber spectrum data are comprehensively considered, the weight information of different indexes is determined by using the fusion weighting method, the foreign fiber spectrum data are optimized based on the interval intuitionistic fuzzy aggregation operator, and a scientific method is provided for predicting the optimal detection spectrum of the foreign fibers in the cotton.

The invention belongs to the technical field of vehicle stability control, and particularly relates to a vehicle stability control strategy optimization method based on a fuzzy logic theory. The method comprises the following steps: firstly, determining a control strategy alternative scheme, an evaluation criterion and a decision maker according to a preset target, calculating each attribute evaluation value and constructing an initial evaluation matrix; secondly, language evaluation given by a decision maker is converted into an intuitionistic fuzzy value; then, determining the weight of each decision maker based on a trust performance function, determining the weight of each evaluation index based on an entropy weight method, and performing normalization processing on the initial evaluation matrix; and finally, based on the constructed evaluation matrix, the decision maker weight and the evaluation index, the TOPSIS method is combined for application, alternative control strategies are sorted and selected, an optimal scheme is determined, an evaluation result has very high robustness, and the sorting problem that a traditional TOPSIS method is difficult to process information containing uncertainty and is easily influenced by subjective factors is avoided.

The application belongs to the field of data management, and discloses a data center load elasticity regulation potential evaluation method and device, which comprises the following steps: performing scale unification processing on operation information collected from a data center, combining an attention mechanism driven feature selection algorithm to screen out key indicators; designing and calculating the objective weights of each core evaluation indicator, combining a multi-dimensional coupling operation of an intuitionistic fuzzy comprehensive evaluation model to obtain the migration level of each task; calculating the proportion of the total power load of tasks determined as high and medium migration levels in the current total load of the data center, and when the proportion exceeds a preset threshold, using a baseline load curve of the data center to solve a multi-constraint optimization model and calculate the elasticity regulation interval of the power load; taking the generated evaluation data as independent evidence to perform data fusion; and according to a deviation correction type GBRT algorithm, correcting the fused evaluation results to output the load elasticity regulation potential evaluation results.

The invention discloses a data missing processing method in large sample analysis simulation evaluation, and relates to the field of data processing in a simulation evaluation process. The method comprises the following steps: constructing a simulation evaluation data matrix, converting the simulation evaluation data matrix into an intuitionistic fuzzy matrix, converting a non-missing index value into an intuitionistic fuzzy index value, determining a reference index set, and filling missing values in the intuitionistic fuzzy matrix to complete data missing processing; according to the method, intuitive fuzzy processing is carried out on simulation data through the characteristic of the hesitation degree of the intuitive fuzzy set, then missing data is filled based on the intuitive fuzzy set algorithm, and finally missing simulation data is restored through the filled intuitive fuzzy number; the method not only can reasonably fill up data missing in simulation, but also eliminates unit and magnitude differences among simulation indexes, and is easy to implement.

This invention relates to the field of integrated defense and early warning technology for clustered targets, and discloses a clustered target threat early warning method based on intuitionistic fuzzy game theory and consensus decision-making. This method collects raw data from multiple sensors and quantifies it into an intuitionistic fuzzy set to generate a clustered integrated decision matrix; calculates the degree of consensus and hesitation potential energy; when consensus is insufficient, it generates resource focusing instructions to drive sensors to adjust physical parameters and perform feedback correction to form a consensus closed loop; it constructs a strategic conflict model to perform game-theoretic linkage analysis to solve for optimal attribute weights and calculates a dynamic early warning threshold; finally, it calculates the final early warning score based on the MABAC algorithm, compares it with the dynamic threshold to trigger an alarm, and outputs a dynamic interpretation vector. This invention solves the problems of decision oscillation and poor adaptability to fixed thresholds in complex electromagnetic environments by using physical information synergy enhancement and strategic game threshold drift mechanisms, thereby improving the accuracy and interpretability of early warnings.

The application discloses a strong Stackelberg game strategy generation method based on an intuitionistic fuzzy set, and the method comprises the following steps: acquiring a topology structure of an infrastructure network, letting a defender be a forerunner, determining strategy sets of an attack party and the defender, and constructing a complex network strong Stackelberg game model; determining an index representing network connectivity, calculating the income of the attack party and the defender under various strategy profiles in the complex network strong Stackelberg game model, and thus obtaining an income matrix; constructing a hyperbolic membership function and a non-membership function by using an intuitionistic fuzzy set determination method; converting the income matrix into an intuitionistic fuzzy set income matrix by using the hyperbolic membership function and the non-membership function; converting the solution of the complex network strong Stackelberg game model into the solution of a nonlinear programming problem, obtaining a mixed strategy Nash equilibrium solution, and thus obtaining the strategy optimization results of the attack party and the defender.

The embodiment of the application provides a kind of method and system for identifying air target based on fuzzy inference, it is related to target identification technical field.The method for identifying air target based on fuzzy inference includes: obtaining the multiple flight data corresponding to target aircraft at multiple times;According to the fuzzy processing of multiple flight data by preset flight parameter, generate multiple input variable fuzzy data;According to the multiple input variable fuzzy data obtained by preset intuitionistic fuzzy inference model and multiple output variable fuzzy data;The comprehensive identification result is obtained by fusing multiple output variable fuzzy data.The method for identifying air target based on fuzzy inference can realize the technical effect of the accuracy of air target identification.

The invention belongs to the technical field of civil aircraft avionics system equipment reliability, and provides a knowledge-data collaborative driving multi-dimensional reliability evaluation method for a standby storage battery pack of a civil aircraft avionics system. The method comprises the following steps: constructing a systematic multi-dimensional reliability evaluation index system for the standby storage battery pack of the avionics system of the civil aircraft; performing weighting on the evaluation indexes by adopting a big language model and a knowledge graph knowledge-improved CRITIC data collaborative driving intelligent method; and comprehensively evaluating the standby storage battery pack of the avionics system of the civil aircraft based on TOPSIS fusing the intuitionistic fuzzy set and the cosine similarity. According to the method, a systematic evaluation system is constructed, knowledge and objective data are fully fused, respective advantages of knowledge-data dual drive are played, accurate evaluation of the reliability of the standby storage battery pack of the avionics system of the civil aircraft is realized, traditional experience dependence is eliminated, and the reliability of the standby storage battery pack is improved. And a theoretical support is provided for accurately identifying civil aircraft avionics system reliability key equipment.

The invention relates to the technical field of data processing, and provides a dual-creation event scoring method and system based on a type-2 fuzzy model and LLM, and the method comprises the steps: constructing a dual-creation event scoring index system, and obtaining a project evaluation criterion; the importance of experts is calculated through linguistic variables represented by intuitionistic fuzzy numbers, and the comprehensive weight of the project evaluation criterion and the project average score corresponding to the project evaluation criterion are calculated according to the weight of each expert; constructing an interval type-2 fuzzy number fuzzy decision matrix and calculating a positive foreground value and a negative foreground value of each item; fusing the weight of the Type2-Fuzzy model and the integration weight of the large language model, and calculating an accumulated foreground weight; and calculating a comprehensive foreground value according to the accumulated foreground weight and sorting the items. According to the method, the scoring result is more objective, the scoring robustness is remarkably improved, the method adapts to scoring requirements of different competitions and fields, subjective deviation is reduced, the scoring efficiency is improved, and fairness and consistency are ensured at the same time.

The invention discloses an intelligent supplier selection method and system, and belongs to the technical field of enterprise resource management and decision support. The system comprises a supplier resource library module used for storing and managing data of suppliers; the supplier admission preliminary screening module is used for aggregating qualitative evaluation of a plurality of decision-making experts based on a possibility distribution hesitation fuzzy language set model, and processing data of suppliers according to a preset comprehensive evaluation value threshold value to obtain potential suppliers; the evaluation index system management module dynamically configures a differentiated performance evaluation index system comprising three dimensions of economy, society and environment for different types of suppliers in the supplier resource library module; the comprehensive evaluation engine module is constructed based on an intuitionistic fuzzy set theory; and the supplier portrait module is used for visually displaying the comprehensive information and the evaluation result of the supplier. According to the method, the defects of high subjectivity, single index and insufficient fuzzy information processing capability in the existing supplier evaluation method are overcome.

The invention discloses a dam seepage safety state assessment method and system, and belongs to the technical field of dam safety monitoring. Firstly, an intuitionistic fuzzy set is generated according to data of each monitoring point, and the dynamic reliability is calculated; carrying out step-by-step fusion to obtain an interval value intuitionistic fuzzy set of the monitoring project and the dam part; and finally, fusing again to obtain a comprehensive evaluation interval value intuitionistic fuzzy set of the whole dam, thereby completing safety state evaluation. According to the method, uncertainty is represented through the interval value intuitionistic fuzzy set, information conflicts are processed in combination with the DSmT theory, effective fusion of multi-source heterogeneous monitoring data is achieved, and the accuracy and reliability of dam seepage safety state evaluation are remarkably improved.

The application discloses a complex network game attack strategy optimization method based on intuitionistic fuzzy, and the method comprises the following steps: acquiring the topological structure of an infrastructure network, determining the strategy set of an attacker and a defender, and constructing a basic model of a complex network game; determining an index representing network connectivity, calculating the income of the attacker and the defender in the basic model of the complex network game under various strategy profiles, and thus obtaining an income matrix; using an intuitionistic fuzzy number determination method to construct a hyperbolic membership function and a non-membership function; converting the income matrix into an intuitionistic fuzzy set income matrix by using the hyperbolic membership function and the non-membership function; converting the solution of the basic model of the complex network game into a linear programming problem solution, obtaining a mixed Nash equilibrium solution, and thus obtaining the attack strategy optimization result.

A nonlinear intuitionistic fuzzy support tensor machine-based fault diagnosis method for marine diesel engines is proposed. Firstly, the multi-source sensor signals are converted into time-frequency images, and then grayed and cropped. Finally, the coupling structure information in the time domain, frequency domain and spatial domain is fully mined by stacking and reconstructing the tensor samples along the forward slice. Secondly, a nonlinear non-membership function is designed to construct an intuitionistic fuzzy set, and the score of each tensor sample is obtained to highlight the contribution of different samples and alleviate the impact of noise on the model. Thirdly, the tensor robust principal component analysis is used to accurately recover the low-rank feature tensor without noise from the original noisy tensor sample. Finally, the nonlinear intuitionistic fuzzy support tensor machine model is established, and the inner product is performed with the low-rank feature tensor without noise instead of the original tensor, which avoids the loss of structural information and coupling information of multi-source monitoring signals and enhances the robustness of the model to noise, thus effectively improving the fault diagnosis performance of marine diesel engines.

The invention discloses a power transmission project scheme determination method considering carbon emission and cost, and belongs to the field of power grid construction, and the method comprises the steps: calculating an estimated carbon emission amount and an estimated cost value of each alternative power transmission project scheme according to configuration parameters in each alternative power transmission project scheme, and calculating the estimated carbon emission amount and the estimated cost value of each alternative power transmission project scheme; determining an interval intuitionistic fuzzy number of each alternative power transmission project scheme; determining a positive ideal solution and a negative ideal solution according to the interval intuitionistic fuzzy number of each alternative power transmission project scheme, and calculating compromise solution index values of each alternative power transmission project scheme according to the positive ideal solution, the negative ideal solution and the interval intuitionistic fuzzy number of each alternative power transmission project scheme; and finally, screening out an alternative power transmission project scheme with the minimum compromise solution index value as a target power transmission project scheme of the to-be-constructed area. By implementing the application, the problem that the carbon emission environmental influence factors are not considered in the power transmission project scheme selection process in the prior art can be solved.

Aiming at the problem of low efficiency of expert classification method caused by expert heterogeneity in group decision making, this paper proposes an intuitionistic fuzzy group decision making method based on confidence-bias classification. Firstly, a hierarchical calculation strategy with confidence priority is proposed, using high-confidence subgroups as local benchmarks to avoid the interference of low-quality opinions on the consensus benchmark. Secondly, a composite bias index containing Euclidean distance and directional deviation is proposed, which combines with the confidence to classify experts into four types: core type, innovative type, ordinary type and adjustment type. On this basis, an adaptive feedback mechanism based on the coupling of confidence and bias is designed, and different consensus guidance strategies are implemented for different types of experts. Numerical examples and comparative analysis show that this method can effectively obtain accurate decision results, and retain high-confidence heterogeneous opinions in the consensus reaching process, thus ensuring the efficiency of consensus while effectively preserving high-confidence decision information.

The invention discloses an index screening method in an analysis simulation evaluation process, and relates to the field of data processing in the simulation evaluation process. The method comprises the following steps: constructing a simulation evaluation data matrix, converting the simulation evaluation data matrix into an intuitionistic fuzzy matrix, converting a non-missing index value into an intuitionistic fuzzy index value, determining a reference index set, and filling missing values in the intuitionistic fuzzy matrix to complete data missing processing; according to the method, intuitive fuzzy processing is carried out on simulation data through the characteristic of the hesitation degree of the intuitive fuzzy set, then missing data is filled based on the intuitive fuzzy set algorithm, and finally missing simulation data is restored through the filled intuitive fuzzy number; the method not only can reasonably fill up data missing in simulation, but also eliminates unit and magnitude differences among simulation indexes, and is easy to implement.

The application discloses a method for generating infrastructure network attack and defense game strategy based on multi-index fusion, and has the characteristics that the method comprises the following steps: acquiring the topology structure of an infrastructure network, determining the strategy set of player 1 and player 2, and constructing an infrastructure network game model; calculating the payoff matrix of player 1 and player 2 in the infrastructure network game under various strategy profiles respectively by taking three network performance indexes of the maximum connected piece scale, network efficiency and clustering coefficient; constructing three pairs of membership functions and non-membership functions according to the preference of a decision maker; converting the payoff matrix into an intuitionistic fuzzy set payoff matrix by using the three pairs of membership functions and non-membership functions, and obtaining a final payoff matrix by using an intuitionistic fuzzy weighted aggregation operator for weighted fusion; and combining the intuitionistic fuzzy set theory to convert the solution of the infrastructure network game model into the solution of a nonlinear programming problem, so as to obtain the mixed strategy Nash equilibrium solution of player 1 and player 2.