A forecasting model of RBF neural network based on genetic algorithms optimization

A new method of gas emission forecasting based on the optimized RBF network is presented. In this method, genetic algorithm (GA) is applied to optimize the position of data centers, widths, and weights of the RBF network, so forming a GA-RBF model. The principle and algorithms of neural network are introduced. The simulation results show that the improved RBF neural networks has high precision, with reliable accuracy, good convergence rate and fast network training speed. Compared with the traditional RBF and BP networks, the method is more efficient and feasible.