Optimized Grey RBF Prediction Model Based on Genetic Algorithm

When combining grey system with RBF neural network, local optimization and convergence problems are still existed, so genetic algorithm is introduced to assist the modeling of grey neural network in this paper. Firstly, genetic algorithm is employed to solve the parameters of improved GM(1,1) with Lagrange´s value theorem, and then RBF neural network is parallel connected to compensate errors. A new dynamic prediction model integrating genetic algorithm and grey RBF, for short GA-GRBF is proposed. This new model with preferable structure and parameters is applied to simulation and analysis of time-displacement data of wind response. The comparative experiment results show that this model is capable of predicting a small sample of data accurately, easily and conveniently.