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Traditional forecast method has a disadvantage for the all-aroundconsideration,such as complication of algorithm, forecast precision,real-time application. There is a general consensus that the lack of a effective method to meet the case.So in this paper there will be a discussion on the new model base on fuzzy-neural network. Fuzzy-neural network is incorporated into a new paroxysmal accident forecast model as a fuzzy logic and neural network.The selection of input parameters are analyzed with necessary considerations accorded history data and emergent events to reduce calculation time and improve the forecast precision
Traditional forecast method has a disadvantage for the all-aroundconsideration, such as complication of algorithm, forecast precision, real-time application. There is a general consensus that the lack of a effective method to meet the case.So in this paper there will be a discussion on the new model base on fuzzy-neural network. Fuzzy-neural network is incorporated into a new paroxysmal accident forecast model as a fuzzy logic and neural network. The selection of input parameters is analyzed with necessary considerations accorded history data and emergent events to reduce calculation time and improve the forecast precision