Using Dynamic Fuzzy Neural Networks Approach to Predict Ice Formation

Abstract

AbstractA prediction model of ice formation based on dynamic fuzzy neural network (D-FNN) combined with particle swarm optimization algorithm (PSO) are proposed. This method is applied to forecast the freeze-up date and break-up date of the Yellow River. The experimental results demonstrate that D-FNN can be used as a prediction system for the length of ice formation and the accuracy of forecasting is superior to those of support vector machine(SVM) and fuzzy optimization neural network(FONN). It is suggested that D-FNN is an effective and powerful tool for ice forecasting.Keywordsdynamic fuzzy neural networks(D-FNN)PSOice forecastingsupport vector machine(SVM)fuzzy optimization neural network(FONN)