67 results about "Fuzzy number" patented technology

The invention relates to the technical field of intelligent production and manufacturing, in particular to an energy-saving fuzzy cascade scheduling method and system for regional gathering cooperative production, and aims to solve the composite problems of supply chain cascade scheduling heterogeneous factory resource allocation, multi-stage time accumulation effect, uncertainty interference and the like in regional cooperative transformation in the manufacturing industry. According to the method, a double-layer collaborative optimization framework is assisted through integrated learning, the uncertainty of quintuple interval fuzzy quantization processing, transportation and assembly time is adopted, an initial Q value matrix is generated through a pre-training layer, self-adaptive operator selection is achieved in combination with a dynamic decision-making layer, and local search, damage recombination and genetic operation are executed by multiple sub-groups. According to the method, the energy-saving second-class fuzzy distributed flow shop and multi-flexible job shop cascade scheduling problem model is effectively defined, three-segment coding and full-process energy consumption calculation are supported, and the overall scheduling efficiency and the energy efficiency balance capability of the regional aggregation industry are remarkably improved.

The invention discloses an automatic driving acceleration test method and device and a storage medium, and the method comprises the steps: carrying out the deconstruction of a scene according to the construction demands of an automatic driving test scene, and extracting the static environment information needed by the test scene and the dynamic parameter distribution of traffic participants; static environment information and dynamic parameters of traffic participants are sampled, and a scene is extracted into a plurality of scene sections; scene section generalization generation is realized by using a conditional table adversarial generative network; through each generated scene section, according to scene variable parameter distribution, behavior uncertainty is captured by using a triangular fuzzy number, and a complete fuzzy track sequence is expanded; constructing an automatic driving high-risk fuzzy test scene in combination with the static environment information and the fuzzy trajectory sequence; therefore, not only is the coverage rate of the test scene improved, but also the pertinence and authenticity of the test are enhanced, and more effective support is provided for safety performance evaluation of the automatic driving system in a complex environment.

The invention discloses a heterogeneous cluster parallel multi-stage fuzzy job scheduling method, which comprises the following steps of: receiving a processing request which is submitted by a user and contains multi-stage jobs, and modeling task execution time, data transmission time and request deadline into triangular fuzzy numbers, constructing a scheduling model taking the minimization of the total lease cost and the minimization of the request tardiness as targets; carrying out global exploration by adopting an improved second-generation non-dominated sorting genetic algorithm to generate parent and offspring populations; based on population similarity threshold judgment, dynamically triggering local search guided by a multi-agent near-end strategy optimization algorithm, and adaptively selecting a local search operator for each individual to generate an adjacent population; combining various populations, performing non-dominated sorting and crowding distance calculation, and screening out a new generation of populations; and iterating the process until convergence, and outputting a Pareto optimal solution set. According to the method, the problem of multi-target scheduling with fuzzy time variables in a heterogeneous environment is effectively solved, and the quality of a scheduling scheme and the algorithm search efficiency are improved.

The invention discloses a vertical take-off and landing field site selection method based on a fuzzy multi-objective optimization model, and relates to the technical field of low-altitude traffic, and the method comprises the steps: constructing a fuzzy number of a travel demand, and converting the fuzzy number into a deterministic interval; constructing a multi-target site selection model according to the deterministic interval; constructing a solving algorithm of the multi-target site selection model; searching a Pareto optimal solution set of the multi-target site selection model by using a solution algorithm; and determining the site selection of the vertical take-off and landing field according to the Pareto optimal solution set. According to the method, fuzzy parameters and operation uncertainty are considered, so that the multi-target site selection model still has relatively high stability in different scenes, and the scientificity, the practical feasibility and the long-term robustness of a vertical take-off and landing field site selection scheme can be improved by solving the multi-target site selection model.

The invention relates to the technical field of train wireless network communication, in particular to an information security risk assessment method for a train wireless network control system, which comprises the following steps of: establishing an attack tree model according to a risk assessment object, assessing the occurrence possibility of a security event by using a triangular fuzzy number, analyzing attack paths, and calculating the interval probability of each attack path, the method comprises the following steps: obtaining a point probability according to an attack path interval probability, calculating an attack occurrence possibility, evaluating a security event influence by using a fuzzy analytic hierarchy process, calculating a security event risk value by quantifying the occurrence possibility and an influence value of the security event, and determining a risk level and a security level of a system according to a system risk evaluation value. And formulating corresponding protection requirements. According to the method, the information security risk of the train wireless network control system is effectively evaluated and managed, a basis is provided for formulating an effective security protection strategy, and the overall security capability of the train wireless network is improved.

The invention relates to a lithium ion energy storage prefabricated cabin risk toughness assessment method based on a fuzzy Bayesian network model. According to the method, real-time operation data, including risk factors such as battery voltage, current, temperature, available capacity, dew point temperature, dust concentration, air velocity and altitude, of the energy storage prefabricated cabin and equipment state data of a battery management system, a fire prevention system and a gas monitoring system are collected. Through processing and calculation of the data, key risk indexes related to the fire risk are determined, and the fault probability of each system is calculated. A risk level of a risk index is converted into a fuzzy number by using a fuzzy set theory, and then the fuzzy number is converted into a prior probability through a left-right fuzzy sorting method. In combination with historical statistical data of the energy storage prefabricated cabin, a Bayesian network total probability formula is used to calculate the probability of fire occurrence, and a reverse reasoning mechanism is used to identify a risk factor which is most likely to cause the fire. And quantitative and dynamic evaluation of the fire risk of the energy storage prefabricated cabin is realized.

The invention relates to a hesitant fuzzy number-based high-voltage circuit breaker operating mechanism voiceprint state detection method and device, and a medium. Extracting features of an original voiceprint data sequence of the high-voltage circuit breaker operating mechanism, wherein the features comprise a Mel-frequency cepstrum coefficient, short-time energy and a zero-crossing rate; forming a symptom feature vector by the symptom parameters, inputting the symptom feature vector into a fuzzy depth residual shrinkage network, constructing a membership function, and outputting a membership value of each state; constructing hesitant fuzzy numbers according to the membership values to form a collective hesitant fuzzy evaluation matrix; determining the evidence weight of each input evaluation model through an optimal-worst method, deriving a state risk weight through a TOPSIS method in combination with a language Z number, and performing weighted fusion on the collective hesitation fuzzy evaluation matrix to obtain a health index; and dividing the health indexes into normal, attention and dangerous health levels by adopting a K-means clustering algorithm. Compared with the prior art, the method has the advantages of high accuracy, high robustness, high flexibility and the like.

The invention discloses a traffic dynamic shortest path distribution method and system based on a triangular fuzzy number weight, and relates to the technical field of intelligent traffic systems.Fuzzy information in a path evaluation attribute is represented through a triangular fuzzy number, a comprehensive weight is analyzed and calculated in combination with deviation maximization and a moisture value, and the decision reliability is effectively improved; a K-Means algorithm is adopted to perform dynamic path search, and through a representative vertex subset pre-calculation and increment updating strategy, the path retrieval efficiency is remarkably improved; a travel time prediction model related to departure time and real-time flow is established, and accurate response to accidental congestion is realized; and finally, outputting an optimal path scheme through a multi-objective decision-making method. Compared with a traditional algorithm, the speed is improved on a real road network data set, the path distribution accuracy is improved, meanwhile, the path safety, comfort and efficiency are effectively balanced, real-time path planning under a large-scale road network is supported, and an efficient solution is provided for intelligent traffic management.

The invention belongs to the technical field of industrial facility safety assessment, and particularly discloses an overdue service pressure pipeline risk assessment method and terminal equipment, and the method comprises the steps: constructing a fault tree with the failure of a pressure pipeline as a top event; obtaining a fuzzy number corresponding to a plurality of expert ratings of each bottom event in the fault tree, and determining a relative consistency degree of the expert ratings according to the fuzzy number; clustering the fuzzy number by using a similarity clustering method, and determining an optimal relaxation factor according to a clustering result; determining the failure probability of each bottom event according to the relative consistency degree of expert rating and the optimal relaxation factor; and determining the failure probability of the top event according to the failure probability of each bottom event. According to the method, the optimal relaxation factor is determined by combining the fuzzy number of expert rating, and the relaxation factor is improved, so that the influence of subjectivity is remarkably reduced, and the reliability of risk assessment of the overdue service pressure pipeline is greatly improved.

The invention discloses a ship plane segmentation workshop fuzzy scheduling method, which comprises the following steps of: firstly, establishing a ship plane segmentation fuzzy scheduling model, adding uncertainty of processing time to the traditional scheduling model, and representing the processing time by using a triangular fuzzy number; secondly, improving the Harlisia eagle algorithm, introducing nonlinear decreasing escape energy and simulated annealing temperature parameters, solving the problems of premature convergence and falling into a local optimal solution of the algorithm, and improving the quality of an initial population by adopting an improved NEH algorithm and chaotic mapping; and finally verifying the validity of the algorithm through a reference function, and applying the optimization method to an engineering example. The method is helpful for improving the efficiency of a ship plane section processing workshop, and has important practical significance.

The invention relates to the technical field of data processing, and discloses a roadway average air volume prediction method and system. The method comprises the following steps: acquiring roadway parameters to obtain resistance interval data; quantifying the air volume uncertainty to obtain an air volume interval range; converting into a triangular fuzzy number to obtain air volume fuzzy distribution data; obtaining average air volume fusion data through weight operator fusion; and air volume prediction data is obtained based on historical sequence error correction. The prediction accuracy of the average air volume of the roadway is improved.

The invention provides a sewage treatment effect real-time evaluation method based on multi-dimensional indexes, which comprises the following steps: firstly, an index monitoring subsystem adopts a dynamic weight sliding window sampling algorithm to collect three kinds of multi-dimensional indexes of water quality, microorganisms and energy consumption; secondly, constructing a fuzzy comprehensive evaluation system, and introducing an improved triangular fuzzy number comment quantization algorithm to determine a factor set and a comment set of'excellent, good, medium and poor '; thirdly, calculating each index weight vector by adopting a grey correlation-analytic hierarchy process coupling algorithm, and ensuring that the weight fits the relevance between the index importance and the actual performance; constructing a fuzzy evaluation matrix, and calculating the membership degree of the index to the comment set through a sectional self-adaptive membership degree function generation algorithm; and finally, calculating a comprehensive evaluation result by using an evidence theory-fuzzy matrix fusion algorithm, and determining an evaluation grade according to a maximum membership degree principle. The method solves the limitation of traditional single index evaluation, improves the evaluation accuracy and real-time performance, and provides support for stable operation of a sewage treatment system.

The invention discloses a lithium iron phosphate battery fault diagnosis algorithm. The algorithm comprises the following steps: collecting an information source data set of lithium iron phosphate battery faults; a genetic algorithm is adopted to search the information source data set, a search result serves as an initial clustering center to be input into a fuzzy C-means clustering algorithm for means clustering, and the clustering number and distance measurement are determined; the expert weight is calculated by using the distance measurement of the trapezoidal fuzzy number, and the attribute weight is calculated by using a deviation maximization method; calculating positive and negative ideal solutions based on the expert weight; and based on the attribute weights and the positive and negative ideal solutions, calculating group benefits, personal regret values and compromise compromise solutions to obtain a fuzzy fault sequence. According to the method, the genetic algorithm is combined with the FCM, the FCM is prevented from falling into a local minimum value in the iteration process, and finally the search result of the genetic algorithm is used as the initial clustering center of the FCM, so that the fault recognition rate of the algorithm is improved.

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 application discloses a waiting time constraint batch processing pipeline crane scheduling method based on an improved slime algorithm and belongs to the field of intelligent scheduling of industrial production. The method comprises the following steps: a scheduling model is constructed, the waiting time fuzzy interval is defined by a trapezoidal fuzzy number, and the maximum completion time is minimized as the target; the waiting time uncertainty is accurately characterized by the fuzzy interval, and the fluctuation range of the waiting time in actual production is completely covered; based on the model, a hybrid improved slime algorithm is used for solving; a matrix coding and One-Hot mapping are adopted to adapt to the discrete scheduling scene; a good point set initialization method is introduced to construct an initial population, and multiple scheduling schemes are obtained; and a double tabu table strategy is combined to optimize the local search efficiency and convergence stability. The application is superior to traditional genetic algorithms, discrete slime algorithms and other comparative algorithms in terms of solution quality, convergence speed and robustness, can efficiently adapt to the crane scheduling demand of process-type industries, and provides a stable and reliable solution for multi-crane collaborative scheduling in a complex uncertain environment.

The application claims a data integrity audit matching method based on psychological perception and preference, comprising the following steps: S1: calculating the subjective and objective weights of each evaluation index, and calculating the subjective and objective combination weights of the index based on the weights, and then calculating the weight of each audit scheme by using the improved Topsis comprehensive evaluation method; S2: calculating the user preference weight by using the triangular fuzzy number and Topsis method according to the user preference set, and integrating the weights of the two; S3: quantitatively calculating the comprehensive preference value of both parties according to the demand preference of the audit task and the execution preference of the audit resource, and calculating the preference utility value matrix of both parties; S4: calculating the perception utility value matrix of both parties based on the improved disappointment theory; S5: standardizing the perception utility value matrix, taking the maximization of the standard perception utility value of both parties as the optimization goal, constructing a double-objective optimization model, and solving the model. The application effectively improves the comprehensive satisfaction of both parties in the case of considering the psychological factors and preferences of both parties.

This application relates to the field of data processing technology and discloses a method and system for predicting average air volume in roadways. The method includes: collecting roadway parameters to obtain resistance range data; quantifying air volume uncertainty to obtain the air volume range; converting it into triangular fuzzy numbers to obtain fuzzy air volume distribution data; fusing it using a weighted operator to obtain fused average air volume data; and obtaining predicted air volume data based on historical sequence error correction. This application improves the accuracy of average air volume prediction in roadways.

This invention discloses a method, apparatus, medium, and equipment for constructing quality control charts based on fuzzy numbers, belonging to the technical field of quality supervision information systems. The method includes: obtaining key quality characteristics corresponding to key processes in the manufacturing process, wherein these key quality characteristics are controlled by control charts; defining fuzzy numbers that satisfy conditions based on the key quality characteristics corresponding to the key processes, and determining the possible value range of these fuzzy numbers; and constructing a control chart corresponding to the uncertain quality characteristics by performing quality factor analysis on the key processes in the manufacturing process, based on the fuzzy numbers that satisfy the conditions, the possible value range of these fuzzy numbers, and the uncertain quality characteristics in the production process. The apparatus, medium, and equipment can be used to implement this method. It can accurately determine random errors in the manufacturing process and more accurately reflect the actual product quality situation.

The application discloses a kind of nuclear power equipment value chain manufacturing risk assessment methods.The present application determines risk group and risk factor in nuclear power equipment manufacturing from risk database;Adopt hesitating fuzzy language term set method, define a set of risk grade evaluation language set, define semantic function as conversion standard;According to risk group, risk factor and risk grade evaluation language set, obtain the evaluation information of each nuclear power equipment value chain manufacturing risk factor from risk database;The evaluation information is converted into triangular fuzzy number and aggregated, the risk importance and risk grade of each risk factor and risk group are determined, and the overall risk importance and risk grade are determined.The present application effectively and accurately processes fuzzy information in risk assessment, comprehensively analyzes the risk importance of each risk factor and risk group, and provides a systematic method for developing nuclear power equipment value chain manufacturing risk assessment.

The application relates to a kind of vehicle engine system electromagnetic vulnerability evaluation methods, belong to electromagnetic environment effect evaluation field.Establish the engine system bayesian network fault model, get the triangular fuzzy number corresponding to the fuzzy expression of the failure correlation between each node in the bayesian network fault model through semantic contrast table, calculate fuzzy conditional probability, convert it into interval grey number conditional probability;Determine electromagnetic stress probability density function and component sensitivity threshold probability density function, calculate component layer interval grey number failure probability, and calculate engine system interval grey number failure probability in combination with interval grey number conditional probability.Affirmative effect is: determine the weight of each sensor through fuzzy analytic hierarchy process, solve the shortcoming that traditional analytic hierarchy process is more subjective, combine grey system theory and fuzzy theory with bayesian network, can more accurately express the uncertain information in the whole evaluation process and carry out failure probability calculation.

The invention provides a two-layer decision optimization method for oil field fire coal coupling biomass emission reduction and heat production, and belongs to the technical field of economic environment decision methods, and the method comprises the steps: selecting influence factors of oil field fire coal coupling biomass emission reduction and heat production according to an environment protection target of a first decision maker and an economic profit target of a second decision maker, data are collected; describing the influence factor by adopting a fuzzy number, and calculating an expected value of the influence factor; constructing a two-layer multi-objective decision optimization global model; converting the two-layer multi-objective decision optimization global model into a two-layer single-objective decision optimization global model; and solving the two-layer single-objective decision optimization global model. According to the method, an expected value of a fuzzy number is introduced to describe an influence factor, a two-layer single-target decision optimization global model is established, the model is solved, an optimal decision solution in the coal-fired coupled biomass power generation process is obtained, and objective conflicts among decision makers are solved.

The present application relates to a kind of ship shore end control system risk assessment method based on interval two fuzzy numbers, comprising the following steps: by the function analysis of system, obtain the relevant data including multiple sub-modules / components, assess the failure probability and loss severity of each sub-module / component, wherein the failure probability and loss severity are interval two fuzzy numbers;According to the failure probability and loss severity of each sub-module / component, the fuzzy risk of system or component is estimated using the improved arithmetic operation rule of interval two fuzzy numbers, wherein interval two fuzzy numbers are composed of elements and high, and the arithmetic operation rule of improved interval two fuzzy numbers is obtained by the arithmetic operation rule of the high of unified interval two fuzzy numbers;The deviation degree and similarity of the results under different operation rules are compared and analyzed to verify the results.

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.

The invention belongs to the technical field of aero-engines, and particularly relates to a high-frequency-band signal combined direction finding method based on a full-baseline fuzzy number search method, and the method comprises the steps: 1, selecting any number of array elements of an interferometer direction finding antenna, calculating the baseline length between all array elements, and obtaining an amplitude comparison direction finding error; 2, determining a search boundary of a fuzzy number of the longest baseline according to the baseline length; narrowing a search boundary by using an amplitude comparison direction finding error to obtain a search range; 3, calculating a residual baseline length fuzzy number set corresponding to each fuzzy number in the search range, respectively substituting all the baseline length fuzzy number sets into the loss function, and taking the baseline length fuzzy number set when the loss function is minimum as an optimal fuzzy number set; and step 4, obtaining direction finding results of all baselines according to the optimal fuzzy number set, carrying out weighted averaging on all the direction finding results, and then solving a final incident angle.

The present application relates to train wireless network communication technical field, specifically to a kind of train wireless network control system information security risk assessment method, including according to the object of risk assessment to establish attack tree model, the possibility of security event is assessed using triangular fuzzy number and occurs, attack path is analyzed, and the interval probability of each attack path is calculated, point probability is obtained according to attack path interval probability, the possibility of attack is calculated, the influence of security event is evaluated using fuzzy analytic hierarchy process, the possibility of security event and impact value are quantified, security event risk value is calculated, the risk level and security level of system are determined according to system risk assessment value, corresponding protection requirements are formulated.The present application effectively evaluates and manages the information security risk of train wireless network control system, provides basis for formulating effective security protection strategy, and improves the overall security capability of train wireless network.

The invention discloses a software quality measurement method based on FERMATEAN fuzzy PROMETHEE and quantum particle swarm optimization. The method comprises the following steps: acquiring an original characteristic value of a software class diagram and constructing a composite fuzzy matter element; the fuzzy number is converted into a Fermatean fuzzy number meeting cubic constraint so as to expand an uncertainty representation space; calculating a score function and an optimal membership degree to form a standardized matrix; constructing a fitness function fusing the distinction degree and the balance penalty, and adopting a quantum particle swarm optimization algorithm to adaptively learn an optimal index weight; on the basis of the optimal weight and the optimal membership degree, a net flow value of each object is calculated by using a PROMETHEE method; and calculating a comprehensive evaluation index according to the net flow value and dividing quality grades. According to the method, the limitation of a traditional method in the aspects of fuzzy information description, static empowerment and linear compensation is overcome, and the accuracy, the adaptability and the decision reasonability of software quality measurement are improved.

The invention discloses a multi-stage mixed flow assembly production scheduling optimization method based on a heuristic algorithm. Firstly, a multi-stage mixed flow assembly scheduling model is constructed, production is divided into L stages, each stage contains Jl stations, and a multi-objective function is established. Secondly, initializing a heuristic algorithm framework, and constructing a set of a high-level heuristic (HLH) strategy and a low-level heuristic (LLH) method; through multi-stage iterative optimization, an initial scheduling solution is generated randomly or according to a priority rule, then a new solution is generated by selecting an LLH method based on an HLH strategy, a current solution is updated by using a dominant solution, and inter-stage collaborative parameters are optimized by using a particle swarm algorithm. Data are collected in real time, and a trigger threshold value is dynamically adjusted. And when the scheduling scheme converges or reaches the maximum number of iterations, outputting the optimal scheduling scheme. According to the method, multi-objective optimization and strategy combination are realized through a hyper-heuristic framework, dynamic adjustment and reinforcement learning are performed in combination with a particle swarm algorithm and a triangular fuzzy number, the system coordination is improved, and the method adapts to personalized manufacturing complexity.

The picture fuzzy set-based collaborative filtering recommendation model comprises the following steps: obtaining and cleaning data information from a database to obtain an original rating matrix; based on picture fuzzy set theory, converting the rating matrix into four matrices representing different preference degrees of users, namely, a membership matrix, a neutral matrix, a non-membership matrix and a rejection matrix; fitting the preference matrix by using a BeMF model to learn feature vector information of the users and the items, and obtaining picture fuzzy numbers of the users for the rated items through inner product of the feature vectors; scoring the picture fuzzy numbers by using a scoring function; learning potential global user preferences in historical ratings by using a multilayer perceptron; combining the scoring of the picture fuzzy numbers (fine-grained preference) and the output value of the multilayer perceptron (global preference) to form a comprehensive prediction value and sort the comprehensive prediction value to generate a recommended item list.

The present application relates to the field of Bayesian network, and discloses a method, device, equipment and medium for explosion case scene reconstruction and suspect judgment, which can construct a Bayesian judgment network of the explosion case according to the condition elements, scene elements and consequence elements of the explosion case, generate a prior condition probability table of the Bayesian judgment network based on triangular fuzzy numbers and mean area method, take multiple elements, the correlation between different elements, part of criminal facts, preliminary assumptions, the occurred scene and the unoccurred scene obtained by surveying and analyzing the central scene as reasoning conditions, input the reasoning conditions into the Bayesian judgment network, make the Bayesian judgment network perform scene reconstruction and suspect judgment according to the reasoning conditions and the prior condition probability table, and obtain the coarse-grained criminal facts, fine-grained criminal scene, behavior and investigation suggestions generated and output by the Bayesian judgment network. The present application can effectively improve the intelligent investigation level and reduce the human resource consumption of investigators.