19 results about "Membership function" patented technology

The application provides a CLAHE image blur enhancement method based on a mixed membership function. The method improves the single membership function in the existing CLAHE method based on the fuzzy theory into a mixed membership function, dynamically fuses the exponential and linear membership functions in the threshold clipping process, realizes the differential processing of the flat area and the area rich in details, and thus adaptively adjusts the clipping threshold, so as to solve the problems of the insufficient histogram equalization capacity, the easy amplification of noise and the poor edge retention effect of the prior art. Compared with the traditional method, the image enhancement quality of the method is significantly improved under multiple scenes.

This invention relates to a knowledge and data fusion-driven, interpretable primary headache auxiliary identification method. The method includes: collecting patient information and preprocessing it to obtain a multi-dimensional feature vector; inputting the multi-dimensional feature vector into an interpretable primary headache auxiliary identification model to obtain a probability distribution of headache identification results; outputting the headache type with the highest probability and its identification confidence, and generating a risk warning; wherein, the hierarchical fuzzy logic layer of the interpretable primary headache auxiliary identification model, based on the multi-dimensional feature vector, calculates the fuzzy membership degree of each feature when it belongs to different headache types according to the differentiated membership function of different headache types, obtaining fuzzy membership degree features; the KAN feature fusion network fuses the fuzzy membership degree features with the original vector to obtain classification features; the classifier outputs the probability distribution of headache types based on the classification features. Compared with existing technologies, this invention provides a solution for intelligent headache diagnosis that combines accuracy, robustness, and interpretability.

The application discloses a voltage sag region online identification method and system based on a dynamic fuzzy rule base, and belongs to the field of power system power quality analysis and protection. The method comprises the following steps: calculating initial voltage sag critical points on each line in a power system to generate an initial voltage sag region AOV; acquiring voltage amplitude deviation, phase jump rate and fault point electric distance data of a load point, and performing fuzzy processing on the data by using a membership function to obtain a membership set, inputting the membership set into a TSK fuzzy reasoning model based on a dynamic updating rule base to output a critical point correction amount; and adaptively updating a region boundary according to the initial voltage sag critical points and the critical point correction amount to output an accurate voltage sag region. By introducing a dynamic fuzzy reasoning and online updating mechanism, the application effectively improves the accuracy and adaptability of voltage sag region identification, and solves the problems that existing methods cannot comprehensively consider multiple influence factors and lack online updating capability.

The present application relates to a kind of video enhancement inference method, device, equipment and medium based on fuzzy control, method includes: initialization multiple different scale pre-training video inference model;Define the fuzzy semantic set of input variable and output variable and membership function;Based on prior knowledge, construct fuzzy rule table;Real-time acquisition input data and complete fuzzy inference, and accurate score is obtained by solving fuzzy output by barycenter method;According to the score value range and anti-shake strategy, the optimal video inference model of next frame is dynamically selected.This method makes full use of the continuity characteristics of target between video frames, realizes the dynamic balance of hardware resources and inference accuracy, the utilization rate of GPU is obviously improved, the target detection rate is also obviously improved, and the temperature is stable within the safety threshold, suitable for real-time video scene such as traffic monitoring, unmanned aerial vehicle inspection.

This invention discloses a data security governance method based on data classification and grading, belonging to the field of data security governance technology. The method includes: collecting resource data and classifying it according to structural type; generating standardized resource datasets and preprocessed record resource packages through differentiated preprocessing; performing sensitivity analysis on the standardized data to obtain comprehensive sensitivity values; constructing a four-level sensitive fuzzy set and corresponding normal membership function; calculating and correcting the membership vector; grading according to the maximum membership principle and completing boundary verification; performing correlation analysis on data of the same grade to determine a segmentation template; segmenting to obtain resource sub-data; determining access permission ranges through association analysis; desensitizing the resource sub-data according to the permission range and sharing it; and simultaneously using a full-process dynamic optimization mechanism to adaptively iterate the parameters of each stage. The advantages are: abandoning the fixed threshold grading mode, achieving refined adaptive sensitivity grading, balancing data security and business availability, and forming a closed-loop governance system throughout the entire process.

This application provides a reservoir permeability prediction model generation and prediction method, apparatus, equipment, and medium, relating to the field of petroleum exploration technology. The model generation method includes: generating multiple target data; determining multiple reservoir permeability intervals and their corresponding target datasets based on the target data; constructing membership functions corresponding to the reservoir permeability intervals based on fuzzy logic and determining the parameter values ​​in the membership functions; determining the target sample set corresponding to each reservoir permeability interval according to the membership degree corresponding to each target data under different membership functions; dividing the target sample set corresponding to the reservoir permeability interval into a first sample set and a second sample set, and training the initial reservoir permeability prediction model separately to obtain two target reservoir permeability prediction models corresponding to the reservoir permeability interval. This application can effectively solve the problem of low prediction accuracy in predicting reservoir permeability based on the correlation between porosity and reservoir permeability.

The application discloses a fuzzy path selection method of a routing protocol in a power internet of things, and comprises the following steps: calculating the covering time between system input nodes and the system utilization, and respectively obtaining the node covering time and the system utilization language state membership function; formulating a language rule according to the step, and obtaining the relationship between the input parameter node covering time, the system utilization language state and the output fuzzy probability language state; the language rule of all input and output functions is defined as a language fuzzy limit language; calculating the system output fuzzy probability, and obtaining the fuzzy probability language state membership function; calculating the sum of the cost between each node of each route according to the fuzzy probability; comparing the route cost of multiple routes, and selecting the route with the minimum cost. Compared with the prior art, the application has the beneficial effects that the technology can improve the routing selection efficiency of the power internet of things terminal device, and reduce the service data transmission delay.

METHOD FOR TRANSFORMING A RADIAL BASED NEURAL NETWORK INTO A FUZZY INFERENCE SYSTEM The present invention relates to a method for transforming a radial basis neural network (RBFN) into a fuzzy inference system. This method comprises a step of dividing the network into distinct RBFN subnetworks and then separating (120) each of these subnetworks. A layer of inference nodes is then inserted (130) at the output of the subnetworks, each inference node applying an inference rule, and then the subnetworks with this inference layer are subjected to a training phase (140) on a training dataset. The activation functions of the neurons in the intermediate layer are then degraded (150), those relating to neurons connected to the same node of the input layer being degraded into membership functions representing a partitioning of the input variable space.A fuzzy inference system functionally equivalent to RBFN is finally generated (160) from the membership functions and inference rules previously adjointed. Figure for the abstract: Figure 1.

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.

This invention discloses a fuzzy multi-attribute decision-making evaluation method and system. The method includes defining a hesitant fuzzy language terminology set; determining the evaluation object and its influencing factors based on the hesitant fuzzy language terminology set to form a factor set, and assigning weights to each influencing factor to determine the membership function of each factor; performing fuzzy synthesis operations on the membership function of each factor and its corresponding weights to obtain a comprehensive membership value; and performing fuzzy evaluation on the evaluation object based on the comprehensive membership value to obtain a fuzzy comprehensive evaluation result of the evaluation object. This invention's multi-attribute decision-making method, capable of handling incomplete and imprecise fuzzy information, plays a crucial role in ensuring the rationality and accuracy of investment risk assessment.

The application belongs to the technical field of power quality analysis and evaluation in power systems, and provides a sensitive equipment voltage sag tolerance evaluation method and system considering aging effect. Firstly, a fuzzy membership function of sensitive equipment tolerance is constructed. Then, the equivalent mean and equivalent variance of the equivalent random variable are determined. A state function of the sensitive equipment under voltage sag is constructed. Finally, according to the equivalent mean and equivalent variance, the reliability index of the state function is determined based on the first order second moment, the sensitive equipment failure probability is obtained, and the sensitive equipment voltage sag tolerance evaluation is realized. Wherein, the aging time-varying model of equipment tolerance is established based on Weibull distribution, which is used to describe the change law of the key parameters of tolerance in the fuzzy membership function with the running time. By considering the aging effect, the problems such as serious overestimation of the actual voltage sag tolerance level of old equipment are avoided, and the tolerance of the equipment at a certain time point in the future can be predicted.

The application provides a fuzzy control-based TT&C signal fine acquisition method and device, and belongs to the field of satellite-borne TT&C transponder signal processing. The method comprises the following steps: acquiring a pseudo-code delay coarse estimation value and a Doppler frequency coarse estimation value respectively; determining the value range corresponding to the input variable of the pseudo-code delay dimension and the value range corresponding to the input variable of the Doppler frequency dimension; determining the input fuzzy set of the pseudo-code delay dimension and the corresponding input membership function according to the input variable of the dimension, and determining the input fuzzy set of the Doppler frequency dimension and the corresponding input membership function according to the input variable of the dimension; for each dimension, performing a bias value estimation operation in the fuzzy set corresponding to the input variable of the dimension to obtain the bias estimation value corresponding to the dimension; and determining the fine acquisition value of the dimension according to the coarse estimation value and the bias estimation value corresponding to the input variable of the dimension. The application can improve the estimation accuracy of TT&C signals.

The application discloses a kind of based on fuzzy comprehensive evaluation's advantage seepage channel identification method, it is related to oil reservoir development technical field.The method includes: obtaining oil reservoir related data, screening evaluation index and constructing evaluation index system;Using analytic hierarchy process to determine the weight of each index, and obtaining weight vector;According to the distribution characteristics of each index, membership function is constructed;Membership degree is calculated to each index observation value, and fuzzy relation matrix is formed;The weight vector and fuzzy relation matrix are carried out fuzzy matrix multiplication, and the fuzzy comprehensive evaluation result vector is obtained;Whether there is advantage seepage channel in oil reservoir area is determined according to the comparison result of evaluation value and preset threshold value, and dynamic data and / or numerical simulation result is verified.The application can effectively handle the fuzziness and uncertainty of oil reservoir data, improve the accuracy and reliability of advantage seepage channel identification, and optimize oil reservoir development decision.

This invention relates to the field of wind turbine blade technology, and discloses a method, device, equipment, and program product for predicting the fatigue life of wind turbine blades. Based on a three-dimensional geometric model, this invention analyzes the stress distribution of the wind turbine blade under different wind speeds using transient dynamics, and generates a finite element model of the target wind turbine blade composite material containing different simulated damages, achieving accurate stress calculation under different operating conditions. By using modal analysis and cubic spline interpolation, two indicators are obtained: the strain modal change rate and direct indicators for damage location, improving the sensitivity and accuracy of identifying and locating minor damages. By using these two indicators combined with rainflow counting to generate a stress spectrum, the load characteristics of critical nodes can be accurately extracted. By combining a skewed semi-trapezoidal membership function and a low-amplitude load strengthening function constructed based on fuzzy mathematics theory, the calculated initial total fatigue damage value is corrected, eliminating stress ambiguity and load influence, significantly improving the accuracy of life prediction.

The application discloses a kind of based on power distribution network security situation Multistage fuzzy comprehensive evaluation method, it is related to power grid safety evaluation technical field, including acquisition power distribution network real-time operation data, environmental information and topological structure, combine history operation sequence to construct time series prediction model, output contains the dynamic safety margin sequence of key security index;Based on dynamic safety margin sequence, time attenuation cumulative operator is applied to the historical fuzzy membership degree of bottom layer security index, and the cumulative membership vector representing risk exposure intensity is generated;Call pre-built power distribution network knowledge graph, according to the semantic scene recognition of current operating state of power distribution network and the dynamic safety margin sequence, generate the multistage safety evaluation index subset adapted to current running context;Cumulative membership vector is mapped to the bottom layer security index of the multistage safety evaluation index subset, and the membership function with adjustable boundary parameter is constructed, and the fuzzy membership vector of bottom layer security index under preset comment set is output.

The application relates to the technical field of machining, and discloses a tool intelligent selection method based on a fuzzy ontology, which comprises the following steps: receiving macro-geometric parameters of a target gear and extracting tool nominal parameters to construct an ontology instance; combining micro-feature classification to generate a boundary compensation coefficient and a compression rate factor, performing translation and contraction calculation on a basic trapezoidal membership function model to output a reconstructed trapezoidal membership function; adjusting a model for processing tool nominal parameters by using a degree fuzzy limiting operator to generate a multi-dimensional membership vector set; judging a matching state, generating rough machining and fine machining task individuals when there is a matching conflict, issuing a fuzzy modification instruction to reset the operator strength and performing secondary logical deduction; extracting a minimum comprehensive deviation distance individual after secondary logical deduction as a result output to generate process coordination data. The application decouples the physical performance contradiction under the multivariable constraint condition, avoids logical deadlock in single tool selection and matching, and improves the matching accuracy of a process planning sequence.

This invention relates to a method and system for optimizing the ratio of sewage sludge ash to soil, comprising: estimating future leaching risk based on historical leaching data of heavy metals in the soil using a prediction model; inputting this risk value along with parameters of the sludge ash components and the ratio scheme into a fuzzy inference system with coupled membership functions, wherein the membership function of the key variable can be adjusted according to the value of another variable; predicting the improvement effect through an initial fuzzy rule base; obtaining the recommended ratio using an optimization algorithm; continuously monitoring the actual effect after the scheme is implemented and comparing it with the predicted value to generate a deviation sequence; when the deviation exceeds a stable threshold, automatically identifying the core fuzzy rule that contributes the most to the deviation and adjusting its weight according to the contribution, thereby realizing online updating and self-correction of the rule base, and continuously improving the prediction accuracy and long-term adaptability of the ratio scheme.

The application relates to the field of avionics, and discloses a method and system for friendly behavior prediction and multi-platform autonomous decision-making in communication interruption, which comprises the following steps: constructing a multi-level fuzzy reasoning tree, fuzzy processing multi-source heterogeneous input information to form multiple fuzzy sets; decomposing complex input relations into several subsystems based on a hierarchical fuzzy reasoning mechanism, and obtaining a subtask response benefit value through layer-by-layer reasoning; and fuzzy processing input variables based on a triangular membership function, and predicting a potential task allocation scheme of a friendly formation in combination with a hierarchical rule reasoning mode. The application can realize multi-platform autonomous task allocation without a center, with low dependence and high robustness, and can improve the cooperative decision-making ability and task execution efficiency of formation members under non-perfect information conditions in a complex environment.

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.