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contributor authorParesh Chandra Deka
contributor authorV. Chandramouli
date accessioned2017-05-08T21:08:25Z
date available2017-05-08T21:08:25Z
date copyrightJanuary 2009
date issued2009
identifier other%28asce%290733-9496%282009%29135%3A1%285%29.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/40200
description abstractThe present study aims at the application of the hybrid model, which consists of artificial neural network and fuzzy logic in the reservoir operating policy during critical periods. The proposed hybrid model [fuzzy neural network (FNN)] combines the learning ability of artificial neural networks and the transparent nature of fuzzy logic. The FNN model is found to be highly adaptive and efficient in investigating nonlinear relationships among different variables. The FNN model has been developed to study the behavior of optimal release operating policy on the proposed reservoir in Pagladiya River of the Assam State in India. Here, reservoir operation policies were formulated through dynamic programming. The optimal release was related to storage, inflow, and demand. The advantages of using the FNN model in reservoir release are discussed using the case study.
publisherAmerican Society of Civil Engineers
titleFuzzy Neural Network Modeling of Reservoir Operation
typeJournal Paper
journal volume135
journal issue1
journal titleJournal of Water Resources Planning and Management
identifier doi10.1061/(ASCE)0733-9496(2009)135:1(5)
treeJournal of Water Resources Planning and Management:;2009:;Volume ( 135 ):;issue: 001
contenttypeFulltext


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