Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/7702
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dc.contributor.authorSingh, Jatin Kumar-
dc.contributor.authorUnder the Guidance of Kumar, A. R. Senthil-
dc.date.accessioned2025-08-11T10:04:00Z-
dc.date.available2025-08-11T10:04:00Z-
dc.date.issued2016-
dc.identifier.urihttp://117.252.14.250:8080/jspui/handle/123456789/7702-
dc.description.abstractArtificial Neural Network (ANN) is a very useful data modeling tool that is able to capture and represent complex input and output relationships. The advantage of ANN lies in its ability to represent both linear and non-linear relationships and in its ability to learn these relationships directly from the data being modeled. Modeling of rainfall runoff relationship is important in view of the many uses of water resources such as hydropower generation, irrigation, water supply and flood control. This study is to purposefully develop a rainfall runoff model for rainfall-runoff modeling in Sutlej river basin, India using soft computing techniques such as Artificial Neural Network (ANN), Radial Basis Function (RBF) and Fuzzy Logic. Training and simulation was done using Matlab 6.5.1 software with varying parameters to obtain the optimum result.en_US
dc.language.isoenen_US
dc.publisherNational Institute of Hydrologyen_US
dc.subjectRainfall-Runoff Modellingen_US
dc.subjectSutlej Riveren_US
dc.subjectSoft Computing Techniquesen_US
dc.subjectIndiaen_US
dc.subjectArtificial Neural Networken_US
dc.subjectANNen_US
dc.title22-Project Report on Rainfall-Runoff Modelling of Sutlej River Basin India Using Soft Computing Techniques.en_US
dc.typeTechnical Reporten_US
Appears in Collections:Vocational Training Report



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