11 results about "Fuzzy probability" patented technology

The present invention pertains to the technical field of motorcycles. Disclosed is a motorcycle safety guarding early warning system, comprising: a data acquisition module, used for acquiring real-time operating data of a motorcycle; a risk coefficient fitting module, used for inputting the acquired real-time operating data into a pre-constructed accident prediction model to output a risk coefficient; a fuzzy probability output module, which uses a fuzzy logic algorithm to evaluate the risk coefficient, and calculates the probability of an accident; and an early warning module, which uses a preset safety threshold, and triggers early warning when the probability of accident occurrence is greater than or equal to the safety threshold. Thus, too frequent false alarms are avoided while the sensitivity of early warning is ensured, improving the applicability and reliability.

This invention discloses a smart park load forecasting method integrating seasonal and solar term features, comprising: generating a feature input vector and a meteorological-solar term deviation vector based on current input data; a trained weight calculation module outputting a weight vector and a bidirectional dynamic hidden state vector based on these two vectors; a trained gating network outputting a fuzzy probability distribution based on the weight vector and the bidirectional dynamic hidden state vector; and a trained fuzzy boundary hybrid expert network outputting park load forecast data for a preset future time period based on the weight vector, the bidirectional dynamic hidden state vector, and the fuzzy probability distribution. The expert network includes multiple trained seasonal and solar term sub-networks, each of which uses the knowledge learned during training to predict park load data. This invention can deeply capture the nonlinear spatiotemporal relationships of multi-source data, significantly improving the prediction accuracy, convergence speed, and robustness of the model under complex and variable climate conditions.

The invention belongs to the technical field of industrial equipment pipeline detection, and discloses an industrial equipment pipeline leakage vibration voiceprint detection method and system, and the method comprises the steps: installing a vibration sensor on a pipeline, transmitting a collected voiceprint to a central control system, carrying out NRBO-FMD processing, extracting six general feature indexes of the voiceprint, and calculating a weight vector through a CVITW-CV method. The method comprises the following steps: extracting three chaotic feature indexes of voiceprints at the same time, constructing a VFMF theory to obtain a cross membership matrix, obtaining a fuzzy weighted feature vector, calculating a weight vector and the membership matrix through an LSH-FSVM, outputting a fuzzy probability, and detecting a pipeline leakage degree. The leakage degree of the pipeline can be effectively detected, and the method is suitable for scenes with complex working conditions.

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

This invention discloses a dynamic risk assessment method and system for storage tanks, comprising the following steps: S1, identifying potential risk sources of the storage tank, taking tank leakage as the assessment object; S2, inputting the potential risk sources and their possible consequences into a fuzzy Bow-Tie model to form a preliminary qualitative analysis of consequences and measures; S3, transforming the Bow-Tie model into a Bayesian network based on mapping relationships; S4, having experts score the corresponding risk sources and converting the scores into prior probabilities of the root nodes of the Bayesian network, determining the weights of each expert using the analytic hierarchy process (AHP), and converting the expert evaluation results into fuzzy probabilities to obtain the prior probabilities of the root nodes and determine the conditional probability tables of other nodes; S5, calculating the posterior probabilities and analyzing and determining the priority relationships of failure modes; S6, providing corresponding risk control measures based on the priority judgment results. This method realizes management from risk source identification to control measure output, overcoming the problem that traditional methods cannot cope with complex dynamic environments.

This application discloses a method, apparatus, equipment, and medium for reliability assessment of a battery energy storage power station, relating to the field of battery management technology. The method includes: dividing the performance state of the energy storage battery compartment into four performance states based on the State of Health (SOH) of the battery compartment, and determining the fuzzy probability of the battery compartment in each performance state using fuzzy mathematics theory; dividing the energy storage power station into a four-level model; constructing a general generating function for the energy storage battery compartment based on the fuzzy probability of the battery compartment in each performance state and the SOH corresponding to each performance state; constructing a multi-state hybrid accuracy model for the energy storage power station based on the general generating function of the battery compartment and the topology of the energy storage power station; and conducting a reliability assessment of the energy storage power station based on the multi-state hybrid accuracy model and the reliability index system of the energy storage power station, obtaining the reliability assessment result of the energy storage power station, and realizing the reliability assessment of the energy storage power station.

The application relates to a nowcast effect evaluation method and system, a terminal and a storage medium. The method comprises the following steps: calculating the membership of radar echo data to a set threshold, calculating the probability mean in the neighborhood range of each grid point by using a spatial neighborhood probability method based on the membership, and obtaining the fuzzy probability of each grid point according to the probability mean; calculating the score of the radar echo data based on the score skill of the Gaussian type membership intensity feature (IFSS); assigning weights to the forecast echo data of each time point by using a time neighborhood adaptive weighting algorithm, calculating the probability of each grid point after the weights are assigned by using a spatial neighborhood probability method, and calculating the score skill of the radar echo data based on the time neighborhood adaptive weighting algorithm (TFSS); and calculating the score skill of the radar echo data based on the intensity feature and the space-time feature (TIFSS) according to the score results of the IFSS and the TFSS. The application can realize more objective and reasonable evaluation and test, and solve the problems of early prediction and delayed prediction.

The invention discloses a method for generating a war game deduction map based on a GIS (Geographic Information System). The method comprises the following steps: acquiring a GIS data set, and performing coordinate unification and data clipping processing on the GIS data set to obtain processed standardized geographic data; based on the standardized geographic data, establishing a hexagonal grid on the two-dimensional projection plane by using a grid division algorithm, and adjusting the side length of a hexagonal grid unit of the hexagonal grid according to the elevation variance of each region to obtain a hexagonal grid division result; for each hexagonal grid unit, calculating an area proportion of each ground feature type in the hexagonal grid unit, and calculating fuzzy probability distribution of the ground feature types based on the area proportion; obtaining feature entropy distribution data according to the fuzzy probability distribution; and based on the feature entropy distribution data, performing adaptive symbol generation and rendering processing on each hexagonal grid unit. The technical problem that a map generated by existing war chess deduction is inaccurate is solved.

The present application relates to the field of data verification classification, and more particularly to an information verification method based on big data, which obtains inquiry information published by a user terminal on an interactive platform, compares keywords in the inquiry information with sample labels, identifies ambiguous keywords and standard keywords in the inquiry information, classifies the ambiguous keywords according to corresponding sub-labels of the ambiguous keywords, determines fuzzy probability coefficients of the ambiguous keywords of each category, determines a maximum fuzzy probability coefficient as a probability consistency coefficient, verifies a representation direction category of the inquiry information according to the probability consistency coefficient, selects a feedback mode for the inquiry information according to a verification result, considers the influence of the clarity of the message information on the verification accuracy through the above process, and feeds back the inquiry information according to the verification result, so as to reduce the probability of invalid feedback through data verification.

The embodiment of the invention provides a pipeline failure possibility prediction method and device, and relates to the technical field of risk evaluation, and the method comprises the steps: determining a bottom layer failure factor and a middle failure factor based on the logic relation of each factor on the influence of pipeline failure; taking the bottom layer failure factor as a bottom event, taking the middle failure factor as a middle event, taking the pipeline failure event as a top event, and connecting the bottom event, the middle event and the top event through a T-S fuzzy gate according to a logical relationship to obtain a T-S fuzzy fault tree; and based on the hierarchy of each T-S fuzzy gate, for each T-S fuzzy gate, calculating the fuzzy possibilities of a lower-level event under various harm degrees, and calculating the fuzzy possibilities of an upper-level event under various harm degrees according to the fuzzy possibilities of the lower-level event under various harm degrees. And finally, obtaining fuzzy possibilities of the top event under various harm degrees. Wherein various damage degrees corresponding to the bottom event, the middle event and the top event are respectively and correspondingly set; and constructing a correction factor according to the fuzzy possibilities of the top event under various hazard degrees, and performing correction on the basis of a preset general failure probability by using the correction factor to obtain a pipeline failure probability. According to the pipeline failure possibility prediction method and device provided by the embodiment of the invention, accurate prediction of the failure possibility of non-oil-gas pipelines such as carbon dioxide pipelines is realized.

The invention discloses an AVM picture abnormity analysis and fault tree generation method, medium and equipment, and the method comprises the steps: 1) obtaining reversing picture abnormity record information which comprises a picture abnormity type, a picture abnormity time point and a picture abnormity probability; 2) constructing a fuzzy fault tree model according to a reversing picture display system structure; 3) carrying out qualitative analysis on the picture abnormity fault tree to obtain a structural importance coefficient of each basic event of the reversing picture abnormity fault tree; 4) carrying out quantitative analysis on the picture abnormal fault tree, and calculating the fuzzy probability of occurrence of a fault tree top event and the fuzzy probability importance of a basic event; according to the method, a fuzzy fault tree analysis method is adopted to analyze abnormal pictures appearing in a reversing system, and a theoretical basis is provided for an enterprise to analyze the problem of reversing picture abnormity.