21 results about "Fuzzy decision" patented technology

This invention discloses a method and system for autonomous decision-making control of coal-fired power units under all operating conditions. The method includes: real-time acquisition and intelligent fusion of multi-source heterogeneous data; identification of monitoring blind spots and execution of blind spot data completion or validity verification; construction of an intelligent control system architecture covering all operating conditions of the unit, decentralizing the functions of the plant-level monitoring information system to the production control area; acquisition of electromagnetic radiation interference characteristic parameters and environmental interference characteristic parameters, and implementation of electromagnetic radiation interference suppression or environmental interference correction based on judgment conditions; fusion of a large-scale artificial intelligence model with a dynamic feature decoupling network and a decision knowledge graph to form a quasi-expert fuzzy decision-making system, executing an integrated control strategy of intelligent control, cruise control, and monitoring; and construction of a high-fidelity digital twin parallel system for offline verification and iterative optimization of the control strategy. This invention achieves autonomous decision-making and near-zero human intervention for coal-fired power units under all operating conditions, improving operational safety and economy.

A man-machine collaborative quality detection and early warning system for intelligent factories, comprising an edge visual acquisition terminal, a cognitive anchor generation module and a hybrid intelligent inference engine, the hybrid intelligent inference engine extracts a high-dimensional feature vector of a workpiece image using a residual network and calculates a Mahalanobis distance. When the distance is in a fuzzy decision interval, a man-machine collaboration request is triggered, and a feature heat map is displayed on the terminal. The cognitive anchor generation module receives defect key pixel points labeled by an operator, maps them to a high-dimensional feature space to construct a feature repulsion sphere, and adds the feature repulsion sphere as a regularization term to the loss function of the residual network for online fine-tuning. The scheme corrects the feature boundary in a targeted manner without changing the weight distribution of the model main body, overcomes long-tail defect missed defects, and improves the feature boundary stability of the detection model under continuous production conditions.

This invention relates to a vehicle differential lock control method, terminal device, and storage medium. The method includes: S1: constructing a first fuzzy membership function, a second fuzzy membership function, and a fuzzy rule inference table; S2: real-time acquisition of environmental values, road grade, and road curvature values, obtaining the maximum value of road curvature; S3: obtaining all corresponding first fuzzy intervals and fuzzy values ​​from the first fuzzy membership function based on the road curvature ratio; S4: obtaining all corresponding second fuzzy intervals and fuzzy values ​​from the second fuzzy membership function based on the environmental values; S5: matching the first fuzzy intervals with the second fuzzy intervals to obtain a combined fuzzy value of the fuzzy interval combination; S6: taking the fuzzy interval combination corresponding to the maximum value as the fuzzy decision combination, and obtaining the decision result from the fuzzy rule inference table; S7: controlling the differential lock based on the decision result. This invention achieves timely differential locking of the vehicle in weather conditions such as rain and snow when slight slippage occurs during normal driving.

This invention discloses a method for graded identification and variable spraying of cotton field weeds based on feature weight enhancement, with the following steps: 1. Multi-channel data decoupling and preprocessing: Acquire cotton field images, extract high-frequency edge features using Laplacian transform to construct texture channels, and construct color channels based on RGB components; 2. Heterogeneous feature embedding and dynamic weighting: Map the dual-channel features to a high-dimensional space, and perform nonlinear weighting enhancement on the texture feature matrix based on the difference in edge curvature between cotton seedlings and weeds; 3. Cross-modal feature fusion and accurate identification: Input the enhanced features into an improved Transformer encoder, use a color semantic mask to focus on vegetation areas and suppress background interference, and output a mask for weed category and location from the decoder; 4. Growth parameter extraction and grade evaluation: Calculate the weed pixel coverage per unit area as a growth density index based on the identification results; 5. Graded decision and prescription map generation: Input the weed species, coverage area, and growth density into a fuzzy decision model to determine the disaster level, match the pesticide spraying dosage, and generate a variable spraying prescription map. This invention improves the accuracy of similar weed identification and the system's adaptive capability in complex field environments by using dynamic feature weighting and multimodal fusion.

The application relates to a cross-domain few-shot named entity recognition method based on coupling of Gaussian distribution and Wasserstein metric, which comprises the following steps: obtaining source domain text data and target domain text data to be processed, and respectively performing data preprocessing; obtaining deep hidden layer state features of each word element; generating a multivariate Gaussian distribution representation with position perception capability; constructing a class Gaussian prototype representing the distribution features of each entity category; and finally outputting the predicted entity category of the text sequence to be measured. By establishing the generation condition of the covariance on the basis of the semantic mean position, the application realizes position-perception uncertainty modeling, so that entities close to the fuzzy decision boundary naturally obtain greater variance, accurately cover the effective semantic radius, and even in the case that the feature distribution of the source domain and the target domain is not overlapped, the application can still provide smooth geometric transmission cost, ensures the stability of optimization, and greatly improves the accuracy of cross-domain named entity recognition.

This application relates to a method, system, device, and medium for monitoring user body fluid balance, belonging to the field of biomedical engineering technology. The monitoring method includes: acquiring user body fluid state data collected by sensors in real time and performing timestamp synchronization and drift correction to obtain a calibrated multimodal data stream; constructing a three-dimensional body fluid state tensor from the calibrated multimodal data stream; constructing a body fluid dynamic balance model based on the three-dimensional body fluid state tensor, and performing dynamic balance analysis and anomaly detection to obtain anomaly feature vectors; determining the intervention level based on fuzzy decision rules; generating a corresponding candidate intervention instruction set based on the anomaly feature vectors and the intervention level; inputting the candidate intervention instruction set into the body fluid dynamic balance model to predict changes in user body fluid state, and selecting the optimal intervention instruction based on the prediction results; and driving the execution device corresponding to the optimal intervention instruction to adjust body fluid parameters. This application can achieve comprehensive management and precise regulation of user body fluid state.

This application relates to the field of digital twin technology, and discloses a method, system, and storage medium for park energy management based on digital twins. The method includes: digitally mirroring and reconstructing the park's physical energy system to obtain a three-dimensional digital twin; performing fuzzy semantic modeling and fuzzy decision processing on multi-dimensional energy state information based on the digital twin to obtain intelligent energy scheduling decision data for the park; inputting the scheduling decision data into a differential evolution algorithm for optimization to obtain the optimal energy management strategy; and constructing a prediction engine based on the optimal strategy for time series learning to obtain a digital twin-driven park energy management scheme. This application solves the problem of difficult virtual-real synchronization of park energy systems by constructing a digital twin, further solves the problem of the inability of fuzzy controller parameters to adaptively optimize by using a differential evolution algorithm, and addresses the problem of insufficient time series data processing capability of traditional prediction methods by using a long short-term memory neural network.

This invention discloses an energy management method for hybrid energy storage systems based on fuzzy model predictive control. It constructs a linear variable parameter model predictive control architecture incorporating fuzzy decision-making for closed-loop optimization control. First, an LPV prediction model for the system is established, and the load power sequence is introduced as a measurable feedforward disturbance into the state equation. During the rolling optimization preparation stage, a fuzzy inference mechanism is used to analyze multi-dimensional operating conditions such as system power fluctuations, SOC, and SOV in real time, dynamically adjusting the weighting factors of energy tracking, battery loss, and current smoothing in the cost function to achieve an adaptive trade-off in the control strategy. Simultaneously, a hierarchical setpoint tracking strategy is adopted, intelligently switching the voltage state reference target based on the real-time energy level of the supercapacitor. Finally, based on the time-varying model, dynamic weights, and the reference target, a quadratic programming problem is solved, outputting the optimal control quantity applied to the power converter, thereby significantly improving the system's adaptive coordination capability and overall operating efficiency under complex and variable operating conditions.

The application discloses a kind of offshore high resistance compensation station configuration methods of multi-level sensitivity guide-multi-objective optimization, first build the full system model containing wind power cluster, high-voltage submarine cable and compensation device, establish the multi-objective optimization function and constraint with investment cost, system loss and voltage stability margin as core;Secondly, a three-level mixed sensitivity analysis framework is proposed, and the sensitivity of node voltage to reactive power injection, network loss to compensation capacity and modal stability margin to compensation position is calculated in turn, and the key candidate nodes are selected according to the weight to significantly reduce the search space, and the improved multi-objective particle swarm optimization algorithm is used to search efficiently in the candidate solution space, and the Pareto optimal solution set considering economy and technology is obtained;Finally, the fuzzy decision theory is used to select the scheme with the highest comprehensive satisfaction from the solution set as the final configuration, providing an economic, reliable and efficient engineering solution for the high resistance compensation station site selection and capacity determination of the deep-sea wind power transmission system.

This invention discloses a UAV formation cooperative obstacle avoidance method based on improved fuzzy decision-making, comprising: continuously acquiring the positions of UAVs and the virtual lead UAV using onboard sensors; obtaining position and attitude control commands for the UAV formation through a formation control method based on virtual structure and consistency theory; setting the distance obstacle avoidance range and rotation angle obstacle avoidance range of the UAVs according to their performance, and constructing a fuzzy decision-maker; determining the threat level of the UAVs based on the fuzzy decision-maker and obstacles, and outputting corresponding formation obstacle avoidance decisions; for UAVs that have broken out of formation, adjusting the obstacle avoidance control quantity of the UAVs that have broken out of formation based on the speed obstacle method and the expected obstacle avoidance speed. This invention ensures that the maneuverability of most members is not affected during inter-UAV collision avoidance, improves the stability and safety of the formation, and is more conducive to the execution of formation tasks.

The application provides a mine integrated energy system operation optimization method and system considering equipment importance, and belongs to the technical field of mine energy system optimization. The method comprises the following steps: S1, establishing a mine integrated energy system operation optimization model, including determining a to-be-optimized equipment type, collecting system operation parameters, determining an optimization target and a constraint condition; S2, solving the mine integrated energy system operation optimization model by using a large-scale constraint multi-objective evolution algorithm considering equipment importance to obtain a Pareto optimal solution set; S3, selecting a compromise solution from the Pareto optimal solution set as a final scheduling scheme by using a fuzzy decision method, and issuing the scheduling scheme to corresponding equipment through multiple communication protocols to realize automatic operation of the mine integrated energy system. The application realizes efficient scheduling optimization of the mine integrated energy system by establishing an optimization model, analyzing equipment variable importance and rapidly seeking optimization in a large-scale decision space through an evolution optimization algorithm.

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.

This invention relates to the field of railway engineering schedule management and intelligent decision-making technology, and in particular to a method and system for ranking railway engineering schedule indicators. The method includes constructing a multi-dimensional schedule indicator system, establishing a hesitant fuzzy decision matrix, introducing a β threshold to construct a covering approximate space, calculating attribute dependencies to reduce redundant indicators, reconstructing the matrix, and calculating a comprehensive evaluation value, ultimately achieving a scientific ranking of schedule indicators. This application can effectively handle uncertainties, incompleteness, and attribute redundancy while preserving the multiple hesitancy and fuzziness of evaluation information, thereby improving the efficiency and accuracy of schedule indicator screening and ranking.

The application discloses a kind of vehicle rear wheel's steering control method, device, equipment and storage medium, by gathering comprehensive information package covering vehicle state information, road environment information and driver state information, realize the perception to vehicle operation panorama.Based on this information, current driving condition is identified simultaneously and driver style is judged, so as to lay the foundation for man-machine collaborative control.In addition, two-layer decision structure including upper layer and lower layer fuzzy decision is constructed, so that the final target rear wheel steering angle is obtained.The application decouples the macroscopic adaptation of working condition and driver style with the microscopic accurate tracking of vehicle dynamics, and realizes the steering control that considers both the individualized needs of drivers and accurately tracks the ideal state of the vehicle in complex and variable scenarios by modifying the basic strategy parameters.The technical scheme of the application can be widely applied in the field of vehicle technology.

This invention belongs to the field of robotics technology and discloses a scene recognition method for adaptive navigation of robots. The scene recognition method is based on a data acquisition unit, a data storage unit, and a data processing unit. The data processing unit is located on a host computer. Sensors are installed on the robot, and the data collected by the sensors is uploaded to the host computer. The host computer extracts environmental features and then uses a fuzzy decision system to determine whether the robot's current environment is wide, moderate, narrow, or impassable. Finally, the parameter set of the Dynamic Window Algorithm (DWA) is automatically switched to the parameter set corresponding to the scene. This scene recognition method solves the problems of incomplete environmental perception, delayed parameter adjustment, and low computational efficiency. It achieves intelligent coordination between scene judgment and the parameter set of the DWA algorithm in complex dynamic environments, and has practical engineering value.

This invention provides a combined cooling and heating system for data centers and its control method. By integrating historical data sensing, multi-step prediction, fuzzy decision-making, and real-time control, it achieves intelligent, efficient, and economical regulation of the data center's heating and cooling environment. The system possesses strong predictive and adaptive capabilities, enabling it to respond in advance to load and environmental changes, smoothly switch operating modes, and significantly improve system stability and energy efficiency. In particular, by introducing a heat recovery mechanism, it achieves the cascade utilization of waste heat, further reducing dependence on external energy sources and carbon emissions. Furthermore, the method combining the LSTM prediction model and the fuzzy logic decision-making model used in this invention effectively solves the control challenges of large time delays and nonlinearities in thermal systems, demonstrating good engineering applicability and promotional value.

This invention provides a method and system for safety risk assessment of urban building clusters based on InSAR and fuzzy mathematics theory, belonging to the technical field of urban building cluster safety risk assessment. This invention acquires temporal deformation monitoring data of buildings within a target area using PS-InSAR technology; it traces back to engineering specifications to determine eight risk deformation assessment indicators and their classification thresholds; and calculates the standardized risk index of each assessment indicator through the relative relationship between deformation data and risk level thresholds. Addressing the differences in indicator contribution and the fuzziness of threshold boundaries, it introduces the analytic hierarchy process to determine weights, and combines fuzzy comprehensive evaluation theory to construct an assessment model, outputting the comprehensive risk level of the buildings. This method constructs a systematic and quantifiable risk assessment process, realizing automated assessment across the entire chain of "deformation monitoring - specification benchmarking - fuzzy decision-making," providing reliable technical support for safety early warning of urban building clusters.

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.

This invention discloses an optimization method for a natural gas pressure energy system based on a multi-objective frost algorithm, relating to the field of energy utilization technology. The specific steps are as follows: A comprehensive optimization model is established for the natural gas pressure energy system from three aspects: system efficiency, economic benefits, and environmental benefits. Then, algorithm parameters are initialized and the population is uniformly initialized. Next, a neighborhood structure is constructed by calculating Euclidean distance, and the fitness of each individual is calculated using a weighted sum decomposition method. The quality of local solutions is optimized by combining a frost neighborhood perturbation mechanism. In the stage of generating new individuals, simulated binary crossover and polynomial mutation operators are used, and a hard frost puncture mechanism is introduced to avoid local optima. Subsequently, the population and solution set are updated, retaining non-dominated solutions and maintaining the convergence and diversity of the solution set. Finally, the optimal result is selected by comprehensively evaluating the optimized solution set using the analytic hierarchy process (AHP)-fuzzy decision method. This invention can optimize and improve the performance of a natural gas pressure energy system.

The application discloses a kind of lower limb exoskeleton man-machine collaborative controller design methods of fusing human fuzzy decision, it is related to man-machine interactive control technical field, including: the lower limb exoskeleton dynamics equation of man-machine system containing parameter uncertainty and disturbance is established, and desired trajectory is as constraint and is converted into second-order form;Robust controller is proposed, and stability analysis is carried out to robust controller;A cost functional is proposed, minimize cost functional, obtain optimal fuzzy membership function to realize man-machine cooperation under fuzzy decision;Adjust relevant parameters in system, and analyze the effectiveness of the control method;The collaborative strategy and control method combine human fuzzy decision with mechanical system stability, use human fuzzy decision to regulate the performance of mechanical system in real time to cope with different tasks and working conditions, and the controller has strong robustness and adaptability, and can be used for different control objects.

The application discloses a kind of investment risk assessment model construction method and system, the method of the present application includes determining the relative importance of each index in the investment risk assessment process;According to the relative importance, determine the evaluation index weight of each index in the investment risk assessment process;Determine the hesitant fuzzy linguistic term set, and the hesitant fuzzy linguistic term set is converted into triangular fuzzy number;Based on the triangular fuzzy number, the triangular fuzzy number form of offshore photovoltaic power generation project investment risk level is obtained, and the triangular fuzzy number is defuzzified to process, to construct investment risk assessment model by the triangular fuzzy number after defuzzification and the evaluation index weight.The present application can establish offshore photovoltaic power generation project investment risk assessment model based on hesitant fuzzy linguistic term set and multi-attribute group fuzzy decision to effectively evaluate the investment risk of offshore photovoltaic power generation project.