37 results about "Fuzzy number" patented technology

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 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 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.

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.

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.

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 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 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 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.

The application provides a multi-baseline phase unwrapping method based on accurate intercept correction, and relates to the technical field of radar signal processing, and comprises the following steps: acquiring parameter information corresponding to main and auxiliary images of an interferometric synthetic aperture radar in an observation scene and original interferometric phases, and constructing a reference intercept vector based on the parameter information and an external digital elevation model database; traversing actual intercepts corresponding to all pixels in the observation scene through a sliding window, obtaining a core intercept based on the frequency of the actual intercepts, correcting the core intercept by using the reference intercept vector, and obtaining a corrected intercept set; calculating a fuzzy number by using a limited range search method or a Chinese remainder theorem method based on the corrected intercept set and the number of baselines to obtain a fuzzy value; and calculating an unwrapped phase corresponding to each baseline by using a phase unwrapping equation based on the fuzzy value and the original interferometric phases. In this way, the practicability and reliability of the multi-baseline phase unwrapping method are significantly improved.

The invention discloses a coal-fired unit flexible operation dynamic comprehensive evaluation method and system with adaptive, robust and multi-criterion evaluation, and the method comprises the steps: constructing an evaluation index set through employing a fuzzy Delphi method; based on Kalman filtering dynamic fusion, using a subjective weight calculated by a triangular fuzzy number best-worst method and an objective weight calculated by an entropy weight method to obtain a dynamic subjective and objective combination weight of the multi-dimensional index; a comprehensive evaluation result is obtained by adopting optimal preference coefficients of a Monte Carlo simulation optimization approximation ideal solution sorting method and a grey correlation analysis method, and multi-dimensional dynamic comprehensive evaluation of the wide-working-condition operation state of the coal-fired unit is achieved; two new indexes of the time ranking fluctuation entropy and the cumulative ranking offset area are provided for evaluating the robustness of the comprehensive evaluation method, and it is ensured that the evaluation method is scientific and reliable. According to the method, an effective tool is provided for scientifically evaluating the wide-load operation performance of the coal-fired unit and optimizing the flexible adjustment capability of the coal-fired unit, and the competitiveness of coal power enterprises in the electric power spot market can be improved.

The application provides a water resource scheduling scheme recommendation method and device to improve the reliability and accuracy of the water resource scheduling scheme recommendation result, comprising: generating an original decision matrix based on a to-be-evaluated scheduling scheme and an evaluation index; converting accurate numerical values in the original decision matrix into spherical fuzzy numbers by using a spherical fuzzy set theory to obtain a spherical fuzzy decision matrix; determining a subjective weight of each element based on an analytic hierarchy process, determining an objective weight of each element based on an entropy weight method of the spherical fuzzy decision matrix, and determining a combined weight of each element based on the subjective weight, the objective weight and a preference factor; constructing a weighted normalized spherical fuzzy decision matrix by using a weighted operation rule of the spherical fuzzy numbers based on the spherical fuzzy decision matrix and the combined weight of each element; and sorting and recommending the scheduling scheme by using a technique for order preference by similarity to ideal solution based on the weighted normalized spherical fuzzy decision matrix.

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 a time sequence fusion and classification method based on a quantum evidence theory. The method comprises the following steps: converting a time sequence to a frequency domain based on DFT; screening a front low-frequency component by using TFI; amplitude and phase features are extracted respectively, and a GFN model is established; the CDGFN is constructed to represent the two-dimensional uncertainty at the same time; generating a quantum basic probability amplitude QBPA function represented by a complex value in a quantum evidence theory (QET); using a quantum evidence combination rule (QECR) in the QET to fuse the multi-frequency information to generate quantum basic probability distribution (QBPD); and finally, performing classification decision based on the quantum Pignistic probability in the QET. According to the method, the complex number dual Gaussian fuzzy number (CDGFN) and the frequency domain feature extraction technology are introduced, so that the problems of missing of two-dimensional uncertainty expression, difficulty in time domain alignment, low small sample classification precision and the like in an existing time sequence classification method are effectively solved, and the classification accuracy is improved.

The application relates to a reliability analysis method of a magnetorheological fluid brake based on an ellipsoid model. The method mainly solves the technical problem that a large amount of data is required in a method for describing a failure rate by using fuzzy numbers. The technical scheme of the application is as follows: the magnetorheological fluid brake is composed of a transmission shaft, a bearing, an end cover, a brake shell, an excitation coil, magnetorheological fluid, a brake disc, a sealing ring and a key, and the reliability analysis method comprises the following steps: step 1: adopting a fault mode diagnosis to perform fault layering on the magnetorheological fluid brake and determining a fault damage level; step 2: according to an analysis result, establishing a dynamic fault tree, and modularly decomposing the dynamic fault tree into a dynamic fault subtree module and a static fault subtree module; step 3: according to small sample data, obtaining upper and lower interval extreme values of failure rates of various components, constructing an interval model of failure rates of various bottom events, and further constructing an ellipsoid model of a top event of each fault subtree; and step 4: using a BDD method and a Markov chain to perform qualitative and quantitative analysis and solving on the dynamic fault tree.

The invention discloses a target identification basic probability assignment generation method based on an evidence theory, and the method comprises the steps: calculating a membership degree corresponding to an interval endpoint value through employing a triangular fuzzy number according to a target attribute interval value observed by a sensor, representing a membership degree function of a target attribute as a triple, according to the interval endpoint values, the numerical relationship of the triple and the membership degrees corresponding to the interval endpoint values, obtaining the initial interval membership degrees of the target attribute interval values belonging to the targets; performing normalization processing on the initial interval membership degrees of the various types of targets to obtain basic probability assignment; and according to the detection reliability of each sensor under the interference condition, correcting the basic probability assignment to obtain the basic probability assignment of each sensor after correction of various types of targets. According to the embodiment of the invention, the problem of basic probability assignment of how to convert the detection result into the evidence focus element when the target identification detection value is the interval value in the information confrontation environment is solved.

The invention relates to a national logistics hub emergency function layout double-layer optimization method considering demand uncertainty, and belongs to the field of emergency logistics planning. The method comprises the following steps: firstly, constructing a national logistics hub-emergency material collection and distribution center-demand point three-level network; a bilevel planning model is established, the upper layer takes the minimization of the total cost of the system as a target, the lower layer takes the maximization of the demand satisfaction rate as a target, and the demand uncertainty is processed by a triangular fuzzy number; converting the model into a deterministic form through an expected value operator, converting the double-layer model into a single-layer nonlinear model by using a KKT condition, and linearizing the single-layer nonlinear model into a mixed integer linear programming model through a large M method and a binary variable; and finally, outputting an optimal scheme by using a standard mathematical programming solver. The method solves the problems of mismatching of decision levels, weak uncertainty response and low solving efficiency in the prior art, realizes balance of economic cost and rescue effect, and is suitable for rapid planning of post-disaster emergency logistics.

The application discloses a mismatch signal robust detection method under a main lobe interference background and relates to the technical field of signal processing, and comprises the following steps: obtaining a to-be-detected signal, constructing a multivariate hypothesis testing problem, constructing a penalty detector, solving the multivariate hypothesis testing problem, and obtaining a detection statistic of the to-be-detected signal; in the solving process, unknown parameters are estimated, and the estimation result is used for solving the multivariate hypothesis testing problem; according to the detection statistic, a distance gate estimation result and a fuzzy number estimation result are obtained; whether the fuzzy number estimation result is equal to preset target distance fuzzy area prior information is judged, if the fuzzy number estimation result is equal to the preset target distance fuzzy area prior information, a real target exists in the to-be-detected signal, and a target distance gate position is obtained, and if the fuzzy number estimation result is not equal to the preset target distance fuzzy area prior information, a real target does not exist in the to-be-detected signal. The application can improve the detection performance under a signal mismatch condition.

The invention discloses a comprehensive evaluation method for gas consumption safety behavior capability of catering industry personnel based on fuzzy Bayesian network construction, and the method comprises the steps: determining an evaluation index system, building the evaluation index system based on the statistics and rule analysis of catering gas accidents in 2019-2023, and the cause analysis of the Bayesian network, and employing a plan behavior theory, a factor set source serving as a model construction basis; a model structure construction system is determined, basic factor sets are determined according to the evaluation index system, Bayesian network nodes are determined according to the relation between the factor sets, and an evaluation model is constructed; a data processing system is determined, a questionnaire survey data result is subjected to evaluation level establishment, natural language variable corresponding triangular fuzzy number, equalization and ambiguity resolution processing to obtain a prior probability, and a conditional probability is obtained by applying a Noisy-or Gate model and serves as a data source to be input into a constructed evaluation model; determining a model evaluation system, formulating a gas use safety behavior capability evaluation level of a catering practitioner, obtaining a gas use safety behavior capability evaluation result of a certain place or a person through predictive reasoning, reversely verifying the reasonable feasibility of the model by applying diagnostic reasoning, and obtaining a mutual influence relationship among nodes through support reasoning.

The invention discloses a coal mine gas explosion risk early warning method, and belongs to the technical field of coal mine safety. According to the method, a plurality of risk judgment variables are selected for detonation of a fire source and gas overrun, an explosion risk analysis index system is established, an image acquisition device based on a triangulation principle is designed by applying a machine vision technology, corresponding risk source information is acquired for each risk judgment variable, and an image is enhanced, so that an explosion risk analysis result is obtained. And constructing a risk measurement model based on a Bayesian reasoning network in the field of data mining, determining a node prior probability and a conditional probability through a triangular fuzzy number, and performing Bayesian forward causal reasoning under the condition of considering node variable relation to obtain a gas explosion risk occurrence probability. Meanwhile, the risk influence degree is considered, and a final explosion risk early warning result is generated. The F1 value of the early warning result obtained by using the method is greater than 0.85, which proves that the method can more accurately predict the coal mine gas explosion risk.

The invention provides a biomass co-combustion power plant cooperative control system and method based on fuzzy logic and multi-objective game, and relates to the field of power system automation and energy supply chain management. The system comprises a multi-source data acquisition module, a memory module, a processor module and a cooperative control terminal. The method comprises the following steps: processing uncertainty of a fuel calorific value and an emission factor by using a trapezoidal fuzzy number; under the constraint of the safe blending combustion ratio and the load balance, a power plant operation cost minimization model is constructed, and the optimal fuel ratio is solved; a TOPSIS multi-dimensional evaluation algorithm is introduced, and an optimal operation condition is screened by integrating environmental cost parameters; and on the basis of a Kalai-Smorodinsky equilibrium solver, a resource interaction threshold value for guaranteeing the continuity of the fuel supply chain is calculated. According to the invention, the problem of material interruption shutdown risk caused by large fuel characteristic fluctuation, multi-target decision conflict and unstable supply chain in biomass coupling power generation is solved, and closed-loop intelligent control of low-carbon operation and fuel supply of a power plant is realized.

The embodiment of the invention provides a robot process data processing method and device, and the method comprises the steps: constructing a process parameter hierarchical structure model which comprises a target layer, a criterion layer and a parameter layer; obtaining semantic evaluation of pairwise comparison between process parameters in the parameter layer, matching a triangular fuzzy number scale library according to the semantic evaluation, determining a corresponding comprehensive fuzzy judgment matrix, calculating an initial process parameter weight, and constructing a multi-target optimization model by taking a process quality target and a process efficiency target as optimization targets; determining an initial process parameter population according to the initial process parameter weight and a multi-objective optimization model, and performing non-dominated sorting on the initial population based on an objective function value to obtain an optimal individual set; the high-frequency process parameter combination is extracted from the optimal individual set for clustering analysis, the initial process parameter weight is adjusted according to the process parameter distribution characteristics obtained after clustering, a process parameter weight table is determined, and the industrial robot application efficiency and accuracy can be improved.

The invention provides an intelligent warehouse-in and warehouse-out efficient matching method and system based on an AI algorithm, and relates to the field of intelligent warehousing, and the method comprises the steps: setting an RFID tag on a to-be-warehoused cargo; the data on the RFID tags are read through the RFID reader-writers arranged on all the bins, and the read data are transmitted to the upper computer through the cascade intelligent gateway; the goods resources are scanned regularly through the RFID reader-writer so as to update the database; based on matter element analysis, formally describing warehouse resources; determining the matching condition of the warehouse resources and the resource demander through a matching algorithm based on a triangular fuzzy number by calculating the text similarity and the numerical parameter similarity; obtaining required warehouse resources through a comprehensive matching weight algorithm; and assigning tasks to the intelligent storage robot based on a genetic algorithm. The logistics efficiency of the intelligent warehouse system is improved based on the artificial intelligence algorithm, the resource utilization rate of the intelligent warehouse system is improved, the cost is reduced, and the efficiency and accuracy are improved.

The application discloses a charging pile site selection multi-criteria decision method based on a Pythagorean fuzzy set, and comprises the following steps: obtaining an individual Pythagorean fuzzy decision matrix, then normalizing the matrix, and calculating an average Pythagorean fuzzy decision matrix; calculating the Hamming distance and Chebyshev distance between the normalized Pythagorean fuzzy decision matrix and the average Pythagorean fuzzy decision matrix, integrating the comprehensive distance to determine the expert weight; calculating the group Pythagorean fuzzy decision matrix based on the expert weight, and then calculating the knowledge measure matrix to determine the index weight; by comparing the size of the Pythagorean fuzzy number in the group matrix, the positive ideal solution and the negative ideal solution are determined, then the positive ideal deviation and the grey correlation degree are calculated according to the Pythagorean fuzzy distance measure satisfying the triangular inequality property, the comprehensive score of the scheme is obtained, the scheme is sorted, and the optimal new energy automobile charging pile site selection scheme is obtained.