Research Of The Ice Condition Forecasting Based On GA Artificial Neural Network

River ice condition forecasting is an important problem that is always concerned by people. Because there is no distinct function relation between factors and ice condition, lots of problems have not been solved completely, especially in the forecasting of break up, freeze up, ice jam and ice dam.With the analysis of the appear, disappear and evolvement of the river ice condition, sum up six aspects of the factors that affect the river ice condition, consist of heat factor, drive factor, river channel configuration, people action, effect of up and down stations and direct runoff. Except the river channel configuration is settled in a short period, any big change of one of the factors could be the dominate factor of the ice condition's development.Because of the good appearance in nonlinear mapping,artificial neural network has been applied in Pattern Recognition,artificial controlling,image processing,time series analyst etc.Radial Basic Function(RBF) neural network have a simple structure and training method,also have goog capabilaty of fast convergence.Can Approximate any nonlinear function.Genetic Algorithms(GA) is a algorithm created to simulate biological. Has a broad applicability, as well as the ability to optimize the overall situation.So RBF neural network based on GA is better than BP neural network in theory.RBF neural network model based on GA were founded, to forecast the break up date of Ha'er bin station on Song Hua River,based on the mechanism of the break up and the ice condition data of the station.The principle of the model is to optimize the parameters of RBF by GA and PLS.Then forecast the break up date using the improved RBF.The results showed that the the forecast get Class-A. RBF neural network model based on GA to forecast the break up date is totally feasible.