Jun Yan, Yanfang Liu, Jun Wang, Hui Cao, Haibin Zhao
{"title":"BP Model Applied to Forecast the Water and Sediment Fluxes in the Yellow River Mouth","authors":"Jun Yan, Yanfang Liu, Jun Wang, Hui Cao, Haibin Zhao","doi":"10.1109/CISP.2009.5303781","DOIUrl":null,"url":null,"abstract":"The fundamental of neural network and its application are introduced firstly. Then the main factors which affect the runoff and the sediment transport volume in the problems of the water and sediment fluxes in the Yellow River Mouth during the flood and non-flood period are analyzed. Furthermore, the BP model is set up by using the program in the toolbox of the neural network under the environment of MATLAB. Finally the runoff and the sediment transport volume in Linjin section are forecasted and the forecasting errors are analyzed.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5303781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The fundamental of neural network and its application are introduced firstly. Then the main factors which affect the runoff and the sediment transport volume in the problems of the water and sediment fluxes in the Yellow River Mouth during the flood and non-flood period are analyzed. Furthermore, the BP model is set up by using the program in the toolbox of the neural network under the environment of MATLAB. Finally the runoff and the sediment transport volume in Linjin section are forecasted and the forecasting errors are analyzed.