关键词: GM（1, 1）模型, 径向基函数, 基于遗传算法的灰色RBF预测模型, GA-GRBF模型, 优化, 残差补偿, ,

Abstract: 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.Genetic algorithm is employed to solve the parameters of improved GM（1，1） with Lagrange’s Mean Value Theorem，two new dynamic prediction models integrating genetic algorithm and grey RBF，one is a grey RBF compensation prediction GA-GRBF model，the other is inlaid grey neural network GRBF model.The new models with preferable structure and parameters are 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.

Key words: GM（1, 1）, Radial Basis Function（RBF）, genetic algorithm based grey RBF prediction model, GA-GRBF model, optimization, errors compensation