Utilization efficiency forecasting of moisture content in maize based on particle swarm optimization algorithm and RBF neural network

Utilization efficiency forecasting of moisture content in maize has a great importance to maize production. RBF neural network is able to universal approximation. PSO-RBF neural network which combines particle swarm optimization (PSO) with RBF neural network is proposed to utilization efficiency forecasting of moisture content in maize. Maize fields of the farms in Henan province are applied to study the utilization efficiency forecasting ability of moisture content in maize by the proposed PSO-RBF neural network method. And BP neural network and normal RBF neural network are applied to compare the PSO-RBF neural network method. By analyzing the experimental results, it is indicated that utilization efficiency forecasting ability of moisture content in maize by PSO-RBF neural network than that by RBF neural network and BP neural network.