68 results about "Defuzzification" patented technology

The invention provides an intelligent proportion control method and system for an antistatic agent synthesis process, and the method comprises the steps: fuzzifying real-time parameters through real-time and historical process parameters by using an asymmetric membership function constructed based on data distribution skewness and kurtosis; historical data samples are mapped into graph theory nodes, communities are divided through a community discovery algorithm to generate fuzzy rules, initial weights are set, and an initial rule base is constructed; using a recursive least square method to identify rule consequent parameters, combining redundancy rules according to cosine similarity, and combining a particle swarm optimization algorithm to optimize antecedent parameters; and inputting the fuzzification real-time parameters into the optimized fuzzy neural network, calculating the activation intensity of the rule, adjusting the weighted average weight based on the information entropy of the current activation intensity, and obtaining the proportion control quantity of each component after defuzzification.

The invention relates to the technical field of virtual reality interaction, and particularly discloses a multi-modal fused virtual exhibition hall immersive interaction system, which comprises the following steps of: acquiring real-time multi-modal interaction data of a user and performing synchronous preprocessing; inputting the orientation semantic words into an interval type-2 fuzzy logic system to generate a three-dimensional space semantic membership field; according to the gesture pointing vector and the hand shaking amplitude, a pointing conical area is constructed, two-dimensional Gaussian distribution is established in a layered mode, and a gesture pointing probability field is generated; taking a semantic membership field, a gesture pointing probability field and a gaze point Gaussian kernel density field as independent evidences, introducing a wall boundary and a floor channel as spatial topology constraints, and fusing by adopting an evidence theory combination rule to generate a three-dimensional intention probability distribution field; carrying out gravity center defuzzification processing on the distribution field to extract a navigation target area, and planning a navigation path by taking the current position of the user as a starting point and taking a nearest floor channel entrance as a passing point; according to the method, the problems of multi-mode fuzzy intention understanding and space adaptation are solved.

This application relates to the field of stationary time series analysis and prediction technology, and discloses a fuzzy prediction method for non-stationary time series, including: determining the fuzzy posterior probability corresponding to the current sequence; updating the fuzzy parameters of the fuzzy set based on the fuzzy posterior probability; generating a rule base associated with the updated fuzzy parameters; performing probabilistic defuzzification prediction based on the rule base to obtain the prediction result; updating the model parameters of the Gaussian mixture model based on the prediction error set corresponding to the prediction result; determining the KL divergence corresponding to the prediction error set based on the parameters in the model parameters, the first half error set corresponding to the first half window, and the second half error set corresponding to the second half window; wherein the current window consists of a first half window and a second half window; the prediction error set consists of the first half error set and the second half error set; and performing prediction based on the KL divergence to obtain the output sequence. This solution can meet the practical prediction needs of non-stationary time series.

The application relates to an embedded fuzzy voice control method and system based on language operator quantification, and relates to the field of embedded voice control, which comprises the following steps: collecting a voice instruction of a user; performing voice recognition on the voice instruction to generate corresponding text instructions; performing semantic analysis on the text instructions to extract control variables, action directions and language operators; determining a basic fuzzy set based on the control variables and the action directions; determining a deformation operator according to the language operator; combining the deformation operator and the basic fuzzy set to generate an input fuzzy quantity, and collecting a current physical state value; and obtaining an aggregated fuzzy set based on the input fuzzy quantity, the current physical state value and a fuzzy rule library; performing defuzzification calculation on the aggregated fuzzy set to determine a physical control signal value, and driving a physical device to perform corresponding actions according to the physical control signal value. The application has the effect of meeting the actual needs of users for the delicacy of device adjustment.

The invention discloses an acquisition terminal test case priority ranking method based on a fuzzy analytic hierarchy process, which comprises the following steps of: applying the fuzzy analytic hierarchy process to the field of acquisition terminal test, and quantizing fuzzy evaluation opinions of experts by triangular fuzzy through constructing a'target-criterion-scheme 'hierarchical structure; fusing a multi-expert judgment matrix by adopting a weighted geometric averaging method, and optimizing a criterion weight and performing defuzzification in combination with consistency check; and comprehensive priority scores of the test cases are calculated through weighted summation, a sorting sequence from high to low is generated, and meanwhile, dynamic adjustment during demand change is supported. According to the method, the fuzzy demand quantification accuracy can be improved by 60%, the expert dispute rate is reduced to 8% or below, the regression test error detection efficiency is improved by 40%, and the method adapts to the multi-scene test demand of the acquisition terminal.

The invention is suitable for the technical field of automation control, and provides a follow-up control method, device and equipment and a storage medium, the method comprises the steps that the actual height between a machining head and a plate is obtained, and the current error and the error change rate between the actual height and the preset target height are determined; performing fuzzification processing on the current error and the error change rate to obtain an error membership degree and a change rate membership degree; according to a preset fuzzy rule table, performing fuzzy reasoning on the error membership degree and the change rate membership degree to obtain a proportion-integration-differentiation (PID) gain membership degree; performing defuzzification processing on the gain membership degree to obtain a PID gain increment; and carrying out superposition processing on the gain increment and the PID fixed gain to generate an adjusted control signal. According to the follow-up control method provided by the embodiment of the invention, the PID gain can be adaptively adjusted so as to cope with follow-up control under complex working conditions, and overshoot or insufficient follow-up response is avoided.

The invention discloses a fuzzy control power dynamic adjustment method of a charging pile node and a related device. The method and the device are used for improving dynamic adaptability and operation stability when the charging pile node is controlled. The method comprises the following steps: carrying out preprocessing calculation on feedback data to obtain a characteristic quantity; performing nonlinear composite deviation calculation on the characteristic quantity of each charging pile node to obtain a comprehensive state deviation; performing fuzzification processing on the comprehensive state deviation and the characteristic quantity to obtain a membership degree value; calculating the trigger intensity of each fuzzy rule according to the membership value, updating the weight of each fuzzy rule based on the trigger intensity to obtain a target weight, carrying out weighted aggregation on the output of each fuzzy rule, and carrying out nonlinear output correction after defuzzification through a centroid method to obtain a target adjustment coefficient; calculating adjustment power corresponding to the charging pile node according to the target adjustment coefficient; and performing unification correction on the adjustment power of each charging pile node according to the total demand power to obtain target power.

The invention relates to a blast furnace molten iron temperature prediction and regulation method, and belongs to the technical field of blast furnace ironmaking production methods. According to the technical scheme, the method comprises the steps that relevant parameters of the blast furnace molten iron temperature are collected, preprocessed, normalized and subjected to feature engineering processing, and a KAN-LSTM-Attention molten iron temperature prediction model is constructed; relevant regulation and control rule knowledge of the blast furnace molten iron temperature is collected, and a rule base containing fuzzy judgment rules and operation rules is constructed in combination with production data and expert experience; and dynamic optimization of the rule base is realized through a fuzzy control method, a molten iron temperature decision model is constructed, fuzzy reasoning and defuzzification operation are performed based on a predicted difference value and related parameters, and an optimal control strategy is selected to realize closed-loop regulation and control of the molten iron temperature. The method has the advantages that the model structure is simplified, deployment feasibility is improved, and accurate control over the temperature of the molten iron in the iron and steel industry is achieved.

The invention discloses a multi-AGV formation keeping control method based on IPSO-fuzzy PID. The multi-AGV formation keeping control method is characterized by comprising the following steps: (1) establishing a dynamic self-adaptive multi-AGV pilot following formation control model; (2) constructing a fuzzy PID controller, setting a fuzzy domain of input and output variables, a membership function and a fuzzy control rule, and obtaining the correction of PID parameters through fuzzy reasoning and defuzzification; (3) constructing an improved particle swarm optimization algorithm with dynamic balance of global search and local optimization, improving the inertia weight and learning factor of a particle swarm, and setting a fitness function; and (4) optimizing the input quantization factor and the output scaling factor of the fuzzy PID controller by using an IPSO algorithm, assigning optimized parameters to the controller, and adjusting the linear velocity and the angular velocity of the following AGV. The formation keeping precision, the response speed and the anti-interference capability can be improved.

The invention discloses a building environment self-adaptive regulation and control method and system based on a space-time attention mechanism, and the method comprises the steps: collecting environment data, such as temperature, flow density, humidity and air pressure, and constructing a three-dimensional thermodynamic model through a dynamic weighted Bayesian collaborative fusion algorithm; the method comprises the following steps: processing environment data by virtue of a space-time cross attention network, and generating a regulation and control priority map with a dynamic space-time weight through operations of dynamic multi-feature embedding, parallel space-time self-attention, cross attention fusion and the like; and the fuzzy-PMV decision engine fuzzifies the atlas and PMV comfort indexes, outputs an equipment regulation and control instruction set through expert rule matching and defuzzification, and realizes closed-loop control from environmental data to equipment actions. Compared with the prior art, the method can accurately analyze the space-time correlation of building environment parameters, adaptively regulate and control equipment, improve the environment comfort and regulation and control efficiency, has the advantages of energy conservation and intelligence, and is suitable for the field of intelligent building environment control.

This invention discloses a fuzzy logic energy-saving control method for a mechanical jigging screen, relating to the field of mineral sorting equipment control technology. The method includes real-time acquisition of raw multi-source state data from the equipment, preprocessing to generate a standardized state feature set containing normalized feed load characteristics, particle size distribution feature vectors, bed thickness variation trend characteristics, and motor power spectrum characteristics. This set is then input into a preset fuzzy inference engine, where fuzzy logic operations are performed using a predefined and tuned fuzzy rule base. The output is a fuzzy set of optimal driving parameters covering fuzzy suggestions for screen stroke, stroke frequency, and acceleration. This set is then defuzzified and converted into deterministic driving command parameters. This method enables precise adaptation of the equipment's multi-source operating states and driving parameters, enhances the collaborative adjustment capability of multi-dimensional driving parameters, optimizes equipment operating adaptability, and achieves the technical effects of dynamic matching of operating conditions and energy-saving regulation.

The invention provides an automatic flood monitoring method and system based on SAR (Synthetic Aperture Radar) data. The method comprises the following steps: calculating a basic SAR membership degree according to dual-polarization SAR data by utilizing fuzzy logic; calculating a radar reflection property membership degree according to the ground feature classification result and the monitored SAR decibel value change data by using fuzzy logic, and calculating a hydraulic membership degree according to the hydrological parameters by using the fuzzy logic; defuzzification is carried out on the basic SAR membership degree, the radar reflection property membership degree and the hydraulics membership degree by using a product method, the probability that each pixel is a water body is determined, and a water body probability graph is generated; and predicting a water body range based on the water body probability graph. According to the automatic flood monitoring method and system based on SAR data provided by the invention, the influence of ground objects such as vegetation and buildings on water body extraction is solved, and the interference of other ground objects (such as roofs, playgrounds and roads) with relatively low reflectivity on a water body recognition result is reduced.

The application relates to the technical field of automatic driving, and discloses a control method, a system, equipment and a medium for a mine area automatic driving vehicle, the method comprising the following steps: determining a first road area where a vehicle is located, and acquiring preset road condition parameters of the area and a second adjacent area; combining vehicle multi-type information, outputting a comprehensive fuzzy set through a preset fuzzy rule base, and generating dynamic weights for the two types of road condition parameters through a defuzzification algorithm; based on dynamic weight weighted fusion, obtaining a current road section target basic risk index and a next road section target predicted risk index; acquiring instant vibration data of the vehicle in the first area, and processing the instant vibration data to obtain an instant jolt index; and weightedly fusing the three types of indexes to obtain a fusion control index, and adjusting vehicle driving parameters according to the fusion control index. The application can comprehensively perceive and integrate mine area road conditions and vehicle states, thereby effectively improving the safety and adaptability of automatic driving.

This invention relates to the field of flexible riser risk assessment technology, and more particularly to a method for risk assessment of marine dynamic flexible risers based on fuzzy rule inference networks. The method includes: acquiring a set of historical failure data for flexible risers; conducting a failure assessment on the historical failure data set based on a five-level risk scoring standard to obtain a first assessment result; performing feature fusion processing on the first assessment result based on a preset expert weight standard to obtain a second assessment result; obtaining fuzzy feature values ​​based on a Gaussian fuzzy mechanism and the second assessment result; inputting the fuzzy feature values ​​into a preset fuzzy rule inference network model to obtain a fuzzy set output by the fuzzy rule inference network model; and defuzzifying the fuzzy set to obtain the flexible riser risk assessment result. This invention, through the processing of a fuzzy rule inference network model, can effectively handle the multi-factor nonlinear coupling effects in flexible riser systems, thereby improving the accuracy of risk assessment.

The application relates to a target detection pre-tracking method and system based on fuzzy control optimized particle filtering, and belongs to the field of target tracking. Particle states are predicted, and particle weights are calculated, the particle with the largest weight is regarded as an optimal particle, and the space near the optimal particle is regarded as an optimal region; the distance between the particle and the optimal particle and the particle ratio in the optimal region are calculated and taken as inputs of a fuzzy controller, a moving coefficient is output after a process of fuzzification, fuzzy reasoning and defuzzification; the particle state is updated according to the moving coefficient, and the particle with a lower weight is moved to a high-likelihood region; the iteration is performed for multiple times until the number of particles in the optimal region exceeds a threshold value; and the state of the target is estimated according to the particle state. The application can effectively alleviate the particle impoverishment problem, improve tracking accuracy, control particle movement through the fuzzy controller, be adaptively applied to different environments and scenes, and has good robustness and interpretability, and the rules can be expressed in natural language.

The invention relates to the field of contact lens production equipment, in particular to a tunnel type curing heating system of a contact lens production line, and aims at large inertia and large hysteresis of a tunnel type temperature control system. And outputting related PID parameters according to an inference mechanism and a defuzzification rule, and inferring the PID parameters by using an AI model. Accurate temperature control output is carried out on a tunnel furnace with large inertia and large lag through a fuzzy PID temperature control system, a complex nonlinear relation is fitted through an AI model, fusion is carried out by combining the advantages of the two, and the fused PID control quantity is obtained. The overshoot of the fused PID control quantity is smaller, the adjustment time is shorter, a more complex multi-parameter nonlinear relation can be fitted, more accurate adjustment parameters adapting to the tunnel type curing heating field are obtained, and the anti-interference capability is higher.

The invention discloses a video code rate adaptive adjustment method, device and equipment and a readable storage medium, and relates to the technical field of wireless communication. The method comprises the following steps: acquiring a current video code rate in real time, and calculating a video code rate change rate and a stability index parameter corresponding to the current video code rate according to the current video code rate; fuzzifying the current video code rate, the video code rate change rate and the stability index parameter to obtain a first fuzzy membership degree, a second fuzzy membership degree and a third fuzzy membership degree; carrying out membership degree truncation and defuzzification according to the first fuzzy membership degree, the second fuzzy membership degree and the third fuzzy membership degree to obtain a code rate adjustment value; and adjusting the current video code rate according to the code rate adjustment value. Therefore, on the basis of the current video code rate, the video code rate change rate reflecting the change trend and the stability index parameters, smooth code rate adjustment with proper amplitude is made in advance through fuzzification, membership stage and defuzzification.

The invention relates to an on-load reactor tap switch intelligent voltage regulation method and device based on a fuzzy adaptive algorithm, and the method comprises the steps: carrying out the real-time data collection of a target electric parameter of an on-load reactor, and taking the target electric parameter as the input data of a voltage regulation decision; performing fuzzification processing on the target electric parameter, and converting the target electric parameter into a fuzzy variable; matching the fuzzy variable with a control rule in a fuzzy control rule base, and outputting a fuzzy control quantity; performing non-fuzzification processing on the fuzzy control quantity to obtain a gear adjusting direction and a step length instruction of the tap switch; and a tap switch is driven to switch the position of a tap joint by adopting a gear adjusting direction and a step length instruction so as to adjust the turn ratio of the reactor winding. The method can cope with the frequent dynamic disturbance problems such as distributed power supply output fluctuation and load abrupt change in a power system, does not need to depend on an accurate system model, facilitates the improvement of the voltage regulation precision, and facilitates the meeting of the high-precision power supply demand. Mechanical abrasion of the switch is avoided as much as possible, and service life of equipment is guaranteed.

The application belongs to the technical field and discloses a control method and equipment of a high-speed motor and an electromagnetic bearing system, the method comprising the following steps: selecting input variables and output variables of a fuzzy controller; fuzzifying the input variables and the output variables, determining a quantization factor, a basic domain and a fuzzy domain; defining fuzzy subsets and membership functions in the fuzzy domain of the input variables and the output variables; calculating the membership degrees through the membership functions; substituting the membership degrees into a fuzzy value formula to obtain fuzzy values of the output variables, obtaining accurate control amounts of the output variables through defuzzification; and outputting the accurate control amounts of the output variables to an electromagnetic bearing model for control. The method can effectively reduce the oscillation and vibration of the system, improve the stability of the overall system, and adapt to large disturbances or complex environments.

This invention provides a method and system for controlling construction waste crushing based on load feedback. The method includes: acquiring the stator current signal of the crusher's main shaft motor; extracting the active current component representing torque; constructing a time sliding window sequence; calculating the algebraic difference between the current active current component and a preset target value to obtain the original load deviation; constructing a weighted function to correct the load deviation amplitude; obtaining the load change rate by taking the first derivative with respect to time; building a fuzzy logic controller, using a Gaussian membership function in the fuzzification stage to establish a mapping between sample entropy and the width of the Gaussian distribution, and setting the membership function width in real time; adjusting the fuzzy subset of PID parameters according to fuzzy rules; using the peak-to-mean ratio of the sliding window sequence as an impact factor to weight and correct the centroid method defuzzification results; superimposing the adjustment increment onto the PID reference parameters; and combining the corrected load deviation to calculate the control command and adjust the output frequency of the feed motor inverter. This invention enables multi-dimensional adjustment of the crusher.

The invention discloses a commercial sports event brand image evaluation system and method based on audience viewing angles, and the method comprises the steps: firstly constructing an initial evaluation index library comprising four dimensions of service, organization, personalization and symbols, and sequentially carrying out the fuzzy membership analysis, correlation analysis and discriminability analysis based on the audience investigation data; screening out a key evaluation index set; then determining the weight of each dimension and index by adopting an analytic hierarchy process; thirdly, objective data such as audience subjective evaluation data, media transmission data and economic benefit preliminary data are collected; constructing a fuzzy relation matrix by using the subjective evaluation data, and carrying out secondary fuzzy synthesis operation in combination with the weight to obtain a final fuzzy evaluation vector; and finally, carrying out defuzzification processing on the vector to obtain a comprehensive evaluation value, and carrying out association analysis on the comprehensive evaluation value and objective data to generate a structured evaluation report. According to the invention, scientific, quantitative and comprehensive assessment of the competition brand image is realized.

According to the intelligent control method and system for graphite sagger compression molding, working condition parameters of the mold temperature, the powder filling amount and the pre-pressing pressure are collected in real time, historical data and finished product size stability correlation analysis are combined, the influence weight of each parameter on the size stability is calculated, and the size stability of the graphite sagger is calculated; real-time parameters are converted into membership values through fuzzification processing, hot pressing features are constructed by fusing the membership of the mold temperature and the pre-pressing pressure, the confidence coefficient of the fuzzy rule base is updated online based on the control result of the last period, fuzzy reasoning is conducted through the weight, the membership of the parameters and the hot pressing features, the rule activation intensity is calculated, and the hot pressing accuracy is improved. And generating a dwell pressure compensation value and a pressurization rate adjustment value through weighted average ambiguity resolution, and adjusting a press system through feedback control.

The application discloses a kind of self-regulating reaction kettle temperature control methods based on fuzzy Smith-PID, belong to temperature control technical field, its steps are: first, the first-order inertia model of reaction kettle temperature system is obtained, then the temperature error and error change quantity are fuzzed, fuzzy rule is formulated, then the real-time PID parameter value is obtained by fuzzy rule table, self-regulating control is realized, finally, the Smith predictor model of reaction kettle is obtained by offline test method, and is brought into system to obtain the self-regulating reaction kettle temperature control method based on fuzzy Smith-PID.The method of the application is aimed at the large lag, nonlinearity, strong interference of reaction kettle temperature control system, the self-regulating of controller is realized by the method of fuzzy Smith-PID, and the stability and response speed of system are improved, and the application field of reaction kettle system is widened.

The invention provides a communication queue optimization method and system based on adaptive fuzzy control, and relates to the technical field of communication networks and intelligent control. The method comprises the following steps: monitoring the length and volatility of a sending buffer queue of a lightweight network protocol stack in a remote monitoring system in real time; performing fuzzification processing on the length and the volatility to obtain a fuzzy set; performing fuzzy reasoning on the fuzzy set based on a fuzzy rule table to obtain a fuzzy set of packet sending interval increments; performing defuzzification on the fuzzy set of the packet sending interval increment to obtain a basic control quantity; and correcting the basic control quantity through a self-adaptive adjustment factor to obtain a packet sending interval increment. According to the method, the network transmission efficiency can be improved, and the link stability and the resource utilization rate are improved.

The invention relates to the technical field of novel electric power, in particular to a novel electric power system supply and demand balance effect evaluation method based on fuzzy logic, which comprises the following steps: constructing a hierarchical evaluation index system including power supply reliability, system flexibility, green low-carbon level and supply and demand collaboration degree; generating an interval type-2 fuzzy set by adopting an interval type-2 fuzzy membership function aiming at the uncertainty input index; meanwhile, constructing a fuzzy cognitive map, inputting real-time data by using a long and short term memory network model, and generating a dynamic weight matrix representing a dynamic time-varying nonlinear coupling relationship among the indexes; and finally, inputting the fuzzy set and the dynamic weight matrix into an updating iteration mechanism, carrying out iteration through interval type-2 fuzzy arithmetic operation, outputting a fuzzy state vector, carrying out defuzzification processing on the fuzzy state vector, and generating a comprehensive supply and demand balance effect evaluation value. According to the invention, quantitative evaluation of the supply and demand balance effect of the novel power system under high uncertainty is realized through fuzzy logic.

The embodiment of the invention provides a vehicle automatic headlamp control method and system and a storage medium, and belongs to the technical field of vehicle electronic control. The method comprises the following steps: acquiring an illumination signal output by an ambient light sensor and a running state signal output by a vehicle state sensor, converting the illumination signal to obtain an ambient illumination parameter, and analyzing the running state signal to obtain a vehicle running state parameter; constructing an input fuzzy variable set based on the ambient illuminance parameter and the vehicle running state parameter, and performing fuzzification processing on the input fuzzy variable set according to a preset membership function to generate a corresponding membership value; inputting the membership degree value into a preset fuzzy rule base to execute fuzzy reasoning and defuzzification processing, and generating a headlamp control instruction; and driving a vehicle headlamp execution unit to execute on-off control or brightness adjustment control based on the headlamp control instruction. According to the scheme, the reliability of automatic headlamp control of the vehicle is improved, and smooth self-adaptive control in a complex illumination scene is achieved.

The application provides a kind of commercial vehicle chassis adaptive control method and system, the method includes: through the collaborative training of federal learning framework, the corresponding coupling feature vector is extracted;According to the coupling feature vector, the corresponding nonlinear sliding mode observer is constructed, the load mass change rate and the road adhesion coefficient are introduced as the gain adjustment factor of nonlinear sliding mode observer, and the corresponding observation equation is output;The joint estimation result between load total mass and road adhesion coefficient is calculated through the observation equation, the fuzzy reasoning and the defuzzification operation are combined, and the chassis comprehensive control strategy adapted to different working conditions is generated;The chassis comprehensive control strategy is issued to each actuator of chassis, and the output response data of actuator and the actual dynamics state of vehicle are synchronously collected, the deviation value of ideal state and actual state is calculated, and the adaptive correction of chassis comprehensive control strategy is completed synchronously according to the deviation value.The application can accurately control the vehicle chassis, and improves the control efficiency.

This invention discloses a smart parcel locker location selection method based on IF-WSP. It utilizes interval fuzzy numbers to establish a fuzzy evaluation matrix, defines random floating parameters, and uses these parameters to weight and integrate expert opinions. An improved chaotic mapping function based on nonlinear perturbation is employed. The method calculates cumulative and summative location selection schemes based on evaluation standard weights, generates a chaotic threshold using the nonlinear perturbation chaotic mapping function, and uses this threshold to perform multiple synthesis of the cumulative and summative location selection schemes. The average location score is then used for defuzzification to determine the final location result. Compared with existing technologies, this invention uses fuzzy logic to transform expert opinions into mathematical expressions and combines them with weighted aggregation and multiplication, fully considering the satisfaction of different customers. This results in parcel locker locations that are closer to customer needs, improving the performance of the parcel lockers and demonstrating significant social value and market application prospects.

The invention discloses a metal hydride safety risk multi-level fuzzy evaluation method based on game equilibrium clustering neutralization. The method comprises the following steps: firstly, constructing a natural environment, production process and production personnel management criterion layer system according to a multi-process flow risk, and subdividing specific risk indexes to construct a hierarchical structure; thirdly, organizing experts to compare every two level factors according to a scoring rule to construct a fuzzy judgment matrix, then calculating index weights by using a game theory equilibrium utility function, a clustering neutralization algorithm and a fuzzy analytic hierarchy process, performing normalization, defuzzification by using a gravity center method, solving an average value to obtain a weight vector, and solving a maximum characteristic value; and the weight is ensured to be reasonable through consistency check. And finally, risk index coefficients are calculated and summed to obtain a safety risk score by combining the index weights of all levels and expert scores, and the risk level is determined according to a score interval. The method is systematic, comprehensive, scientific and objective, risk assessment accuracy is effectively improved, and powerful guarantee is provided for industrial safety production.

The application relates to a clock difference prediction method and device, computer equipment and a readable storage medium, comprising: obtaining a to-be-processed clock difference sequence; performing data preprocessing on the to-be-processed clock difference sequence to obtain a standardized residual error sequence; processing the standardized residual error sequence by using a probability-weighted fuzzy time sequence model to obtain a probability-weighted fuzzy time rule set; performing recursive prediction in combination with the fuzzy time rule set to obtain a prediction value set matched with the fuzzy time rule; performing defuzzification processing on the prediction value set to obtain a prediction residual error; performing inverse standardization processing on the prediction residual error and combining the prediction residual error with a trend item fitted and extracted in the data preprocessing process to obtain a target clock difference prediction result. The application eliminates data noise and magnitude difference through data preprocessing, fully captures sequence time sequence characteristics by using a probability-weighted fuzzy time sequence, can effectively improve clock difference prediction accuracy, and provides a reliable clock difference prediction solution for high-precision real-time positioning of a satellite navigation system.