In order to reduce the amount of redundant data in the wireless sensor network and reduce the transmission energy consumption,an adaptive learning rate back propagation data fusion algorithm data fusion algorithm (ALR-BPDFA) based on BP neural network is proposed.The algorithm first sets up the cluster head selection mechanism and introduces a BP neural network model.Ssecondly,feature variables and feature values are set in the network to filter and optimize the collected information.Finally an adaptive learning factor is introduced into the learning rate of the neurons to improve the convergence speed and environmental stability.Simulation experiments show that the new algorithm can effectively reduce redundant data traffic,reduce network energy consumption,and extend network life.

Research on Click Probability Estimation Model Based on Taobao Advertising Data [J]. Journal of Shenyang University of Chemical Technology, 2022, 36(5): 461-467.