A BP neural network prediction model of agricultural economic benefits based on particle swarm optimization algorithm

摘要

According to the multi-input, nonlinear, and volatile data in agricultural economic forecasting model, we proposed a prediction model for the economic benefit of agriculture, combing the particle swarm optimization algorithm and BP neural network. The simulation results show that the model can greatly improve the efficiency and accuracy of processing in agricultural economic benefits information prediction.