{"title":"Wavelet neural network based on BP algorithm and its application in flood forecasting","authors":"Ping Hu","doi":"10.1109/GRC.2009.5255121","DOIUrl":null,"url":null,"abstract":"As is well known, it is the application of runoff flood forecasting that is extraordinary significant for us. A detailed detection of the flood forecasting process has been carried out using powerful artificial neural network in this paper. Learning algorithmof wavelet neural network was produced by extruding it in BP idea.The determination of network hiddenlayer nodes utilizes the medthod of tring fault. Activation function belongs to morlet wavelet function, and the modle of net structure belongs to 371. It is shown that the reliable prediction accury could be provided by using this model for predicting and analysising for the flood data of solar Da in 1996.","PeriodicalId":388774,"journal":{"name":"2009 IEEE International Conference on Granular Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Granular Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GRC.2009.5255121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
As is well known, it is the application of runoff flood forecasting that is extraordinary significant for us. A detailed detection of the flood forecasting process has been carried out using powerful artificial neural network in this paper. Learning algorithmof wavelet neural network was produced by extruding it in BP idea.The determination of network hiddenlayer nodes utilizes the medthod of tring fault. Activation function belongs to morlet wavelet function, and the modle of net structure belongs to 371. It is shown that the reliable prediction accury could be provided by using this model for predicting and analysising for the flood data of solar Da in 1996.