Fuzzy Neural Network Modeling of Reservoir Operation

The 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...

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Bibliographic Details
Published in:Journal of water resources planning and management 2009-01, Vol.135 (1), p.5-12
Main Authors: Deka, Paresh Chandra, Chandramouli, V
Format: Article
Language:English
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TECHNICAL PAPERS
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Summary:The 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.
ISSN:0733-9496
1943-5452
DOI:10.1061/(ASCE)0733-9496(2009)135:1(5)