关键词: 神经网络, 遗传算法, 灰色模型

Abstract:

BP algorithm usually has slow convergence speed and is easy to fall into local minimum value． On the basis of the analysis
and study for the domestic market of air conditioning order． This article proposes a method of the model parameters of grey neural network
optimized by genetic algorithm． By utilizing the property of gray model that the randomness of data can be reduced and the strong
nonlinearity of neural network，the method establishes a non-linear prediction model for air conditioning demand，and the genetic algorithm
is used to optimize it so as to improve the accuracy of forecasting and speed up the degree of convergence． Simulation results indicate
that the algorithm can better solve the problem of air conditioner order forecasting and can be widely apply to similar prediction．

Key words: neural network, genetic algorithm ( GA), gray model ( GM)