32 results about "Fuzzy membership function" patented technology

This invention relates to the field of power system generation scheduling and discloses a method for risk analysis and control of pre-flood energy storage in cascade hydro-wind-solar complementary systems. Taking the pre-flood energy storage as a constraint, a dry-season drawdown model and a flood-season water storage operation rule are established to define simulation criteria. A comprehensive set of indicators, including dry-season power shortages, flood-season water spillage, inadequate year-end energy storage, and wind and solar power curtailment, is constructed to quantify multi-stage, multi-source operational risks. By coupling Monte Carlo simulation with fuzzy membership functions, the method characterizes multidimensional uncertainty scenarios and their probabilities, and analyzes the quantitative relationship between pre-flood energy storage and system benefits, risk probabilities as well as losses. Simulation results demonstrate that precise risk characterization coupled with proper storage control increases annual generation by 580 million kWh while reducing average risk-induced losses by 42%, demonstrating substantial practicality.

The invention discloses a cross-domain HDR image dynamic ghosting removal method fusing statistical offset fuzzy membership, and the method comprises the steps: carrying out the ghosting removal of an LDR image sequence through employing a trained fuzzy statistical cross-domain ghosting removal model, and obtaining a ghosting-free HDR image; according to the model, after an input LDR sequence is subjected to preprocessing and feature extraction, a space context alignment module dynamically aligns non-reference frame and reference frame features through space-channel attention; meanwhile, the LDR image sequence is input into a statistical offset fuzzy membership module, and a membership graph is generated through sliding window statistical analysis and a fuzzy membership function; the aligned features are input into a multi-scale cross-domain cooperative processing module, multi-scale feature extraction and feature fusion are carried out, a frequency attention module is activated through membership graph gating, and global context modeling is introduced into a key region; and finally, outputting a high-quality ghosting-free HDR image. According to the method, fuzzy statistics and cross-domain processing are fused, and accurate ghosting removal and detail reservation in a dynamic scene are realized.

The embodiment of the invention provides a decision negotiation method and device based on a depth deterministic policy gradient. The method comprises the following steps: receiving negotiation scene information input by a first negotiation party; wherein the negotiation scene information comprises a plurality of negotiation topics, a preference value interval for each negotiation topics and a preference weight value for each negotiation topics; for each negotiation topic, creating a invention for the negotiation topic according to the preference value interval and the preference weight value of the negotiation topic; wherein the utility model comprises corresponding trapezoidal fuzzy membership functions when negotiation values are in different preference value intervals, and an overall satisfaction function for performing weighted summation on the trapezoidal fuzzy membership functions of all negotiation dimensions; a first reference value of the first negotiation party is predicted through a pre-trained Actor-Critic network; and receiving a first negotiation value input by the first negotiation party according to the first reference value, and sending the first negotiation value to a second negotiation party, thereby facilitating determination of the negotiation value.

The invention provides a boiler soot blowing control method and a related device, and relates to the technical field of boiler operation control. Performing image processing on the initial image of the boiler heating surface to obtain a processed image, performing mapping operation on pixel coordinates of the processed image and actual reference coordinates of the boiler heating surface to obtain a mapping result, and obtaining a region image corresponding to the soot blower based on the mapping result, carrying out dust deposition identification operation on the regional image to obtain a dust deposition identification result, calculating regional attribute information of the regional image according to the dust deposition identification result, determining a fuzzy membership function boundary value corresponding to the regional attribute information, constructing a self-adaptive fuzzy membership function by using the fuzzy membership function boundary value, and obtaining a self-adaptive fuzzy membership function; and determining a fuzzy quantity corresponding to the regional attribute information by using an adaptive fuzzy membership function, determining a soot blowing parameter of a soot blower corresponding to the regional image according to the fuzzy quantity corresponding to the regional attribute information and the fuzzy rule base, and controlling the corresponding soot blower to perform soot blowing operation according to the soot blowing parameter.

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.

The application discloses a kind of multi-sensor data fusion and online reconfiguration method based on planetary topology structure, including the following steps, construct three-layer multi-sensor data fusion framework based on planetary topology structure, with sensor as outer layer satellite, the subsystem of two two combinations of sensor as middle layer planet, inner layer is main filter;Two-stage fault detection unit is set in satellite and planet layer, sensor fault information is provided by sensor, the effective probability of subsystem is obtained by substituting chi-square test value into fuzzy membership function by subsystem;Filter system reconfiguration table is designed, when fault occurs, the influence brought by fault is reduced online when system reconfiguration is carried out to multi-sensor data fusion system;Finally, global state estimation is completed in inner layer main filter based on the fault information of sensor and subsystem.

The invention provides a fuzzy analytic hierarchy process-based oil-water well extraction control property judgment method and equipment, and relates to the technical field of oil-gas field development, and the method comprises the following steps: determining multiple indexes influencing an oil well end control decision, including daily oil production, daily liquid production, daily water production, water content, single-layer oil production, oil production intensity and the like; all indexes are weighted through an analytic hierarchy process, and statistical analysis is introduced into weight determination, so that weight calculation is more objective and accurate. And mapping each index value into the membership degree of the oil well end control or the water well end extraction by adopting a fuzzy membership function. And the weighted membership degree of each index is synthesized, comprehensive evaluation values of the single well in the two categories of oil well end control and water well end extraction are calculated, and the extraction control property of the well is judged according to the comprehensive evaluation values. According to the method, information of multiple levels and uncertainty factors can be comprehensively considered, the accuracy and scientificity of liquid extraction and water control decision making are improved, and the method is suitable for comprehensive treatment and development optimization of the high-water-content oil field.

The application provides a kind of pumped storage unit water turbine operating condition starting process performance multi-index fusion calculation method, relating to pumped storage power station technical field. Including Step1, data standardization;Step2, using fuzzy membership function to convert the data after standardization into fuzzy evaluation matrix;Step3, calculate information entropy;Step4, calculate variation coefficient;Step5, determine adaptive weight from information entropy in Step3 and variation coefficient in Step4;Step6, calculate starting process comprehensive performance score;Starting process comprehensive performance score is obtained by weighted summation, while introducing nonlinear adjustment factor to enhance the degree of differentiation. Through fuzzy membership function processing the uncertainty of index, using information entropy theory to determine the index weight objectively, and introducing adaptive mechanism to dynamically adjust weight distribution, so as to realize scientific, objective comprehensive evaluation of multi-index system.

The invention discloses a gas turbine power turbine rotating speed compound control method based on SMC-PID. The method comprises the steps that a cluster of state space models is established at multiple steady-state points of a gas turbine, scheduling parameters are selected, a scheduling method based on a weighted fuzzy membership function is adopted, scheduling weights are determined by calculating the correlation degree of the scheduling parameters and the steady-state points, and an LPV model of the gas turbine is established; performing discretization processing on the classic PID control law by taking the rotating speed as a control target to obtain a PID control model; based on the established LPV model, constructing a dynamic sliding mode surface model fusing a power tracking error and a change trend thereof; the basic fuel quantity is obtained according to the PID control model, the fuel flow compensation value is obtained according to the dynamic sliding mode surface model, the basic fuel quantity and the fuel flow compensation value are added to obtain a final fuel flow control signal, and the rotating speed of the gas turbine is controlled. According to the embodiment, the adjusting time is shortened under the typical working condition, the overshoot is reduced, and sliding mode buffeting is restrained; and the rotating speed deviation is controlled and is fast and steady, and the robustness is better.

The invention discloses an intelligent resource scheduling method and system based on water affair data, and the method comprises the steps: achieving the real-time collection and preprocessing of multi-modal water affair data through an edge calculation node, guaranteeing the data quality and safety through an adaptive sampling strategy and differential privacy protection, and achieving the non-tampering evidence storage of the water quality data; a demand prediction model based on a space-time diagram neural network is adopted, accurate prediction of partitioned water consumption is achieved through space-time convolution and a gating attention mechanism, an improved multi-target particle swarm algorithm is adopted, water supply stability, energy consumption minimization and leakage suppression are taken as targets, and an optimal scheduling scheme is screened in combination with a dynamic inertia weight and a fuzzy membership function; virtual deduction is carried out through a digital twin system, pressure abnormity is visualized, an intervention strategy is recommended, pump set operation is optimized in combination with a time-of-use electricity price strategy, and agent adding is dynamically adjusted based on water quality prediction. According to the method, the water supply stability can be improved, the energy consumption and the leakage rate are reduced, and the reliability and economy of a water affair system are remarkably improved.

The application relates to a daily power consumption prediction method based on a fuzzy membership function, which comprises the following steps: step S1: constructing a time sequence of historical daily power consumption and historical air temperature by taking date as an index; step S2: establishing a fuzzy membership function; step S3: taking the maximum Pearson correlation coefficient as an objective function, and optimizing the parameters of the fuzzy membership function through a meta-heuristic algorithm; step S4: converting the historical air temperature and the predicted air temperature into relevant factors based on the optimized fuzzy membership function, and marking the relevant factors as covariates; and step S5: establishing a time sequence prediction model, training the model by using the historical daily power consumption and the historical covariates, and finally inputting the predicted covariates to calculate the daily power consumption prediction value. The application fully utilizes weather forecast data, and effectively improves the accuracy of daily power consumption prediction of a power grid.

This invention discloses a method for constructing a trust mechanism for electricity market transactions based on blockchain, relating to the field of electricity market transaction technology. The specific steps of this construction method are as follows: S100, data collection and feature fusion: collecting electricity user equipment operation data, electricity consumption behavior pattern data, power grid interaction data, as well as electricity market transaction price fluctuation data, historical default records, and power grid operation status data. By utilizing the distributed ledger characteristics of blockchain, this invention achieves encrypted storage and tamper-proofing of multi-dimensional information such as electricity user equipment operation data, electricity consumption behavior pattern data, power grid interaction data, and electricity market transaction price fluctuation data, effectively preventing data forgery and tampering. At the same time, by using fuzzy membership functions to create an initial credit scoring model and combining it with a real-time monitoring and scoring update mechanism, this invention can dynamically adjust the credit scores of trading entities, ensuring the accuracy and timeliness of credit assessment.

The application discloses a ball and link system control method based on fuzzy sliding mode and periodic event triggering, first constructs a state space equation of the system and carries out regular transformation to obtain a standard system model; then, a fuzzy sliding mode switching function is established in combination with a fuzzy membership function, and a periodic event triggering mechanism is designed; on the basis, a periodic event triggering fuzzy sliding mode controller is constructed, an actual sliding mode band is constructed by analyzing a periodic sampling error, state trajectory is ensured to enter the band in a limited time and remain in the band, and the reachability of the sliding mode surface is ensured; then, a controller gain matrix is solved based on stability analysis of the sliding mode, is brought into the controller to complete closed-loop control on the ball and link system, and a system sampling period is established. The application uses the fuzzy membership function to design the sliding mode surface, has lower conservativeness, and uses the periodic sampling to design the event triggering mechanism, theoretically eliminates the Zeno phenomenon, and provides an efficient control scheme for a system with limited network and communication resources.

The invention discloses a land surface remote sensing virtual constellation selection method and device, a medium and equipment. The land surface remote sensing virtual constellation selection method comprises the following steps: retrieving a candidate satellite list meeting requirements from a pre-constructed virtual constellation domain knowledge graph according to an input query demand; generating a plurality of groups of candidate virtual constellations according to the candidate satellite list, and calculating an observation capability index of each candidate virtual constellation; constructing a fuzzy membership function according to a preset fuzzy comprehensive evaluation requirement, and calculating a single-factor evaluation matrix according to the fuzzy membership function; calculating a total score of each candidate virtual constellation according to the single-factor evaluation matrix and the observation capability index of each candidate virtual constellation; and determining a final target virtual constellation according to the total score of each candidate virtual constellation. According to the method, the adaptation degree of the satellite combination and land surface task parameters can be improved, and the satellite resource utilization rate and the observation task planning efficiency are improved.

The invention discloses a method for designing an asynchronous controller of a type-2 switching fuzzy system, which comprises the following steps of: through an IT2 fuzzy set of a prerequisite variable and an emission intensity interval set of a fuzzy rule under an If-Then rule based on an interval type-2 discrete switching fuzzy system of a local nonlinear model; based on a fuzzy reasoning method, constructing a global fuzzy model of the discrete switching nonlinear system; assuming that a switching signal of the global fuzzy model meets the minimum residence time constraint, defining a system timer, and constructing an interval type-2 fuzzy controller dependent on a type-one prerequisite variable division domain; and based on the gain of the interval type-2 fuzzy controller, a closed-loop type-2 switching fuzzy system model with guaranteed cost generalized dissipative performance is obtained. According to the method, different controller structure frameworks are adopted in the asynchronous time period and the synchronous time period, fuzzy member function information of the system is fully utilized to improve the control effect, and the stability and the guaranteed cost generalized dissipation performance of the closed-loop system can be guaranteed.

The invention belongs to the technical field of dynamic defense, and particularly relates to a dynamic defense method and system fused with water conservancy network security situation awareness, so as to solve the technical problems that data isomerism is difficult to process, model static state lacks timeliness, threat prediction is incomplete, and defense decisions are not balanced in an existing attitude awareness method. The defense method comprises the following steps: constructing a multi-layer attack tree model of the water conservancy network; obtaining heterogeneous security data collected by monitoring nodes in a network, quantifying the heterogeneous security data into normalized threat values in one-to-one correspondence with leaf nodes in the model based on an asset vulnerability incidence matrix and a situation element fuzzy membership function, and taking the normalized threat values as conditional occurrence probabilities of the leaf nodes; and traversing all attack paths in the multi-layer attack tree model, and executing an operation on any path. According to the defense method, interference to normal operation of the water conservancy core business is reduced, and balance between safety and business is achieved.

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 invention discloses a coulomb ecosystem health evaluation method and system based on multi-dimensional data, and relates to the technical field of ecosystem health evaluation, and the method comprises the steps: obtaining multi-dimensional monitoring data of a target ecological region, and carrying out the time-space alignment processing, and obtaining the deep features of all dimensions; establishing a causal inference network of deep features, and performing anti-factual inference in combination with time-delay response characteristics to generate a causal association structure; dividing features of a driving layer and a response layer according to a causal conduction path, and calculating a dynamic weight; performing knowledge verification by adopting a priority reconciliation strategy, and establishing a health state reference benchmark; constructing an adaptive fuzzy membership function to obtain a membership function set; and constructing an evaluation model by using the dynamic weight and the membership function set, inputting deep features to obtain a comprehensive health evaluation index, and determining a health level. The method can accurately evaluate the health condition of the coulomb ecosystem.

The invention discloses an intelligent evaluation and measurement integrated system of measurement and control equipment based on a digital twinborn body, and relates to the technical field of industrial automation and digital twinborn. The technical key points are as follows: the system comprises a data acquisition module, a digital twin modeling module, an intelligent index evaluation module, a weight fusion calculation module, a grade scoring reasoning module and a feedback regulation module. The system collects operation parameters of measurement and control equipment through a multi-source heterogeneous sensor, constructs digital twin models in one-to-one correspondence with the operation parameters, and achieves virtual synchronous mapping of equipment states; an index grade evaluation system is constructed based on a fuzzy membership function, subjective and objective weight fusion is carried out in combination with an analytic hierarchy process and an entropy weight method, a comprehensive weight vector is generated, and quantitative evaluation of the equipment intelligence grade is completed through a fuzzy reasoning algorithm. According to the system, parameter adjustment suggestions are further output through an error feedback mechanism, and model closed-loop correction and performance self-adaptive optimization are achieved.

The invention discloses a hotel order fuzzy matching method based on a large model. The method comprises the following steps of 1) collecting hotel order screenshot information of each platform by using a hotel order screenshot mode; 2) constructing an order keyword library based on the hotel order screenshot information; 3) training a graph neural network model by using the order keyword library; 4) acquiring screenshot information uploaded by the user; 5) establishing a fuzzy membership function by using the graph neural network model, and optimizing the fuzzy membership function by using the loss function; and performing semantic supplement on the screenshot information by using the optimized fuzzy membership function, and writing the supplemented semantic features into the semantic content extracted in the step 5) to generate the semantic content without missing. According to the method, semantic rule understanding is realized by calling a large model interface, and meanwhile, fuzzy matching is performed on orders of hotels by applying a fuzzy membership function, so that quick matching of hotel screenshots and hotels is realized.

The embodiment of the application provides a kind of doctor-patient joint decision agent negotiation method and device based on particle swarm algorithm, it is related to doctor-patient joint decision technical field.The doctor-patient joint decision agent negotiation method contains S1, obtains the trapezoidal fuzzy membership function of doctor and patient to n negotiation problems, and the weight of n negotiation problems, and according to trapezoidal fuzzy membership function and weight, constructs multi-objective optimization model.S2, according to multi-objective optimization model, based on belief-desire-intention architecture, constructs doctor agent model and patient agent model.The agent model includes opponent model, bid strategy model and acceptance strategy model.Bid strategy model is used to solve multi-objective optimization model by multi-objective particle swarm algorithm and non-dominated solution distance method, to obtain offer.S3, according to doctor agent model and patient agent model, construct agent-based negotiation model.S4, according to agent-based negotiation model, carry out simulated negotiation, obtain negotiation result.

The invention discloses a fragment block chain credible bookkeeping node selection method supporting fault tolerance. The method is specifically implemented according to the following steps: step 1, initializing a fragment block chain system and nodes; step 2, generating a fragment consensus node set; step 3, fragment bookkeeping node selection and block generation; step 4, fragmentation synchronization; according to the method, the fuzzy membership function and the aggregation signature algorithm based on the threshold are utilized to construct a new fragmentation bookkeeping node selection method to realize a dynamic, fair and fault-tolerant bookkeeping node selection process, and the security and robustness of the fragmentation block chain consensus bookkeeping process can be ensured.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as intelligent security and protection, financial science and technology, medical health and the like, and discloses a decision-making method, device, equipment and medium based on fuzzy logic enhancement. The method comprises the steps of generating logically enhanced multi-modal features based on a preset logic relation, collecting environment parameters, fusing the environment parameters with the logically enhanced multi-modal features to generate a dynamic environment state, generating a current decision strategy based on the dynamic environment state by adopting an adaptive dynamic planning module, and generating a decision instruction, and acquiring an execution result of the decision instruction as feedback information, and updating the fuzzy membership function, the logic relationship and the current decision strategy by using the feedback information. By combining fuzzy processing, logic enhancement, environmental state fusion and dynamic planning optimization, the method can deal with the uncertainty of multi-modal data, and improve the accuracy of decision making in a complex environment.

This invention discloses an adaptive adjustment method for zero-trust dynamic access control policies based on environment awareness. By continuously collecting and standardizing multi-dimensional dynamic contextual information from the subject, object, and operating environment, it breaks through the limitation of traditional methods that only focus on subject attributes. This enables trust assessment to comprehensively integrate multiple factors such as resource sensitivity, network link status, and real-time threat intelligence, thereby truly reflecting global dynamic risks and exhibiting high dynamic adaptability to scenarios such as sudden changes in network environment and zero-day attacks. By using dynamic weights and decay memory algorithms to calculate real-time trust values ​​and combining a mapping mechanism based on dynamic asymmetric threshold intervals and fuzzy membership functions, it avoids the trust level jump problem caused by fixed threshold hard boundary division in existing technologies.

The application is a 5G base station energy-saving control method and system, relates to the technical field of communication, and aims at the problem of excessive use or idling of resources in the prior art.The application provides a 5G base station energy-saving control method, which comprises the following steps: real-time load monitoring, service demand analysis, intelligent decision-making, if it is determined that a component meets a sleep condition, sending a sleep instruction to the component to make it enter a sleep state, and if it is determined that the component meets a wake-up condition, sending a wake-up instruction to the component to make it return to a normal working state.The application accurately determines whether various hardware components in the base station meet sleep or wake-up conditions through an intelligent decision-making algorithm, realizes dynamic optimization configuration of hardware resources, and effectively avoids excessive use or idling of hardware resources.According to different types of hardware components and service demands, the weight coefficients and fuzzy membership functions of various factors can be flexibly adjusted, the accuracy and reliability of prediction are improved, and the application has high scalability and good flexibility.

The application relates to a virtual power plant frequency modulation control method and device based on fuzzy control, wherein the method comprises the following steps: adopting a trapezoidal fuzzy membership function to describe the state of charge of an electric vehicle, indoor temperature and frequency modulation price; establishing fuzzy rules of the electric vehicle and fuzzy rules of air conditioner load; determining the output of the state of charge of the electric vehicle, indoor temperature and frequency modulation price under the fuzzy rules of the electric vehicle and the fuzzy rules of the air conditioner load, weighting and averaging all the outputs to obtain the frequency modulation willingness of each electric vehicle and the frequency modulation willingness of each air conditioner load; taking the minimum signal tracking effect cost and user willingness cost as a target, constructing an intra-day optimization scheduling model; solving the intra-day optimization scheduling model to obtain a frequency modulation control strategy, and adopting the frequency modulation control strategy to perform frequency modulation control on the virtual power plant. The application realizes intra-day second-level control of frequency modulation auxiliary services participated in by the virtual power plant.

The application provides a fuzzy analytic hierarchy process-based oil-water well lifting-control property determination method and device, and relates to the oil and gas field development technical field.The method comprises the following steps: determining multiple indexes affecting oil well end-control decision, including daily oil production, daily liquid production, daily water production, water cut, single-layer oil production and oil production intensity, etc.The analytic hierarchy process is used to weight each index, the weight is determined by introducing statistical analysis, so that the weight calculation is more objective and accurate.Each index value is mapped to the membership degree of oil well end-control or water well end-lifting by using a fuzzy membership function.The weighted membership degrees of all indexes are comprehensively considered, the comprehensive evaluation value of a single well in the "oil well end-control" and "water well end-lifting" two categories is calculated, and the lifting-control property of the well is determined accordingly.The method can comprehensively consider multiple hierarchical information and uncertain factors, improve the accuracy and scientificity of the lifting-liquid control-water decision, and is suitable for the comprehensive management and development optimization of high-water-cut oil fields.

The invention discloses a lower limb exoskeleton man-machine cooperation controller design method fusing human fuzzy decision, and relates to the technical field of man-machine interaction control, and the method comprises the steps: building a lower limb exoskeleton kinetic equation of a man-machine system containing parameter uncertainty and disturbance, taking an expected track as a constraint, and converting the expected track into a second-order form; providing a robust controller, and performing stability analysis on the robust controller; a cost functional is put forward, the cost functional is minimized, and an optimal fuzzy membership function is obtained to achieve man-machine cooperation under fuzzy decision; relevant parameters in the system are adjusted, and the effectiveness of the control method is analyzed; according to the cooperative strategy and control method, the human fuzzy decision and the mechanical system stability are combined, the performance of the mechanical system is regulated and controlled in real time through the human fuzzy decision so as to cope with different tasks and working conditions, and the controller has high robustness and adaptability and can be used for different control objects.

The invention discloses a vehicle-pile-network interaction data fusion method based on a fuzzy mathematical theory, and belongs to the field of intelligent traffic systems and electric vehicle charging infrastructures, and the method comprises the steps: firstly collecting vehicle, pile and network original data, and carrying out the time-space alignment, standardization and abnormal value processing, thereby providing a high-quality basis for subsequent fusion; fuzzifying the key data by using a fuzzy membership function to improve a federated weighted average method to realize data-level fusion to obtain a unified fuzzy data set; on the basis, constructing a five-dimensional feature matrix, extracting key principal components through principal component analysis, completing feature-level fusion, and extracting core features; and finally, constructing a fuzzy rule base, calculating a rule weight by using a Dasarathy model, screening significant and important rules to realize decision-level fusion, and integrating multi-stage results to output final fusion data. According to the method, the data fusion precision and reliability are improved, and city-level vehicle-pile-network regulation potential quantification and efficient cooperative operation are assisted.

The invention discloses an administrative service management method and system based on a cloud platform, and relates to the technical field of administrative service management, and the method comprises the steps: based on a cost range interval, generating a threshold sequence, constructing a nested Hamiltonian, dynamically adjusting a threshold and an annealing path, obtaining a final ground state through QRT evolution, and carrying out the quantum measurement based on the final ground state. Obtaining a quantum state of target Gibbs distribution, verifying an overlapping estimation value, and screening a global optimal scheme; the efficient fusion of heterogeneous data is realized by combining a fuzzy membership function with VGG-16 and BERT models, the semantic matching precision and data processing efficiency of user preferences and service requests are improved, a flow path is optimized based on a directed acyclic graph and reinforcement learning, and a quantum optimization algorithm is introduced, so that the dynamic selection of a global optimal scheme is realized, and the user experience is improved. And the resource allocation efficiency is improved.