3 results about "Neural fuzzy" patented technology

The application provides a vehicle fault diagnosis method and device based on multi-source data fusion and a storage medium. The method comprises: collecting real-time state data and real-time alarm data of a target part, obtaining external environment data and map navigation data; after data preprocessing, the multi-source data set target features are obtained by fusion, the target features extracted from the multi-source data set are input into the adaptive neural fuzzy inference system, the target features are mapped to multiple fuzzy sets, and the member function is used for fuzzification; the rule weight of each target feature is calculated to reflect the fuzzy strength; the neural network learning algorithm is used to train the inference system, the member function and the rule weight are adjusted, the fuzzy output is converted into a specific numerical value or a fault level in the defuzzification process by using the output member function, so that the health state of the part is judged. The application provides a fault diagnosis output with high interpretability, improves the accuracy, and can perform fault diagnosis in a wide range of vehicle operating environments.

This invention aims to provide a smart battery control method for cold chain environments, comprising the following steps: A) Sensor data acquisition, real-time acquisition of ambient temperature T, ambient humidity H, condensate level W, battery voltage U, and battery temperature Tb; B) Data preprocessing; C) Setting preset thresholds, including temperature threshold, humidity threshold, SOC threshold, and insulation resistance threshold; D) Establishing a fuzzy rule base, inputting ambient temperature T, ambient humidity H, condensate level, alarm level, and BMS status into corresponding functions of the fuzzy rule base, outputting various control parameters for control by a controller, while simultaneously providing feedback on the status. An adaptive neural fuzzy control algorithm is used to correct and optimize the above functions in real time, achieving nonlinear dynamic regulation. The method of this invention can effectively solve the technical problems of battery range degradation, high short-circuit risk, and shortened lifespan in cold chain environments characterized by low temperature, high humidity, and easy condensation.

The application discloses a kind of crop precision irrigation method and system based on algorithm fusion, it is related to intelligent agriculture and precision irrigation control technical field, method includes: the time series data of meteorology, soil, crop physiology and irrigation process are collected, carry out exception elimination, missing completion and standardization processing and construct derivative feature;The historical characteristic sequence is input to the bidirectional time series network with attention to obtain time series representation, input neural fuzzy inference network to output future water demand prediction value and corresponding prediction interval, obtain confidence from prediction interval;Water demand prediction value, confidence and crop stress are input to the first layer fuzzy inference to obtain basic irrigation duration;Soil water potential and post-irrigation feedback are input to the second layer fuzzy inference to obtain valve fine tuning amount;Fusion generates irrigation instruction and drives execution equipment.By outputting water demand prediction interval and constructing confidence, the prediction reliability is improved, and by double-layer fuzzy inference, soil water potential and post-irrigation feedback are combined to realize executable and safety protection of irrigation instruction.