Estimation of Reservoir Discharge with the Help of Clustered Neurogenetic Algorithm
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This chapter presents a new approach of reservoir out flow prediction using a clustered neurogenetic algorithm. The algorithm combines the learning ability of artificial neural networks with searching capability of the genetic algorithm. The model is tested on the Panchet reservoir in river Damodar using the historical, hydrological, and water supply dataset. The values of the input parameters are classified into six groups based on the magnitude of the input parameters. The results showed a highly adaptive and flexible investigating ability of the model in prediction of nonlinear relationships among different variables.
KeywordsClassified neurogenetic models discharge model performance multi-reservoirs
The authors would like to acknowledge Dr. Chandan Ray, Retd. Chief Engineer, Irrigation and Drainage Department, West Bengal Govt. and Dr. Debasri Roy, Joint Coordinator, School of Water Resources Engineering, Jadavpur University, West Bengal, India for their valued comments and reviews, which helped in the preparation of the chapter.
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