ICCCES-16

A STUDY OF RECURRENT NEURAL NETWORKS BASED WATER LEVEL FORECASTING FOR FLOOD CONTROL: CASE STUDY ON KOYANA DAM (140591)

DOI :

Abstract : Flood control is crucial task that faces fatal hazards due to fast rising peak flows from urbanization. To lower down the future flood damages,it is imperative to construct an on-line accurate model t o forecast inundation levels during flood periods. Th e regions near Koyna and Krishna basins located in Maharashtra region is selected as study area. In th is approach first step is the analysis of historical hydro logic data by statistical techniques to identify the time span of rainfall affecting the rise of the water level in the floodwater storage pond (FSP) at the regions . Second step is the effective factors that affect th e FSP water level are extracted by the Gamma test. Thirdly,one static artificial neural network (ANN) (Back Propagation Neural Network-BPNN) and two dynamic ANNís

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Modified Date : 2016-01-30

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Mr. Avadho ot S. Idate , Mrs.R.J. D eshmukh , "A STUDY OF RECURRENT NEURAL NETWORKS BASED WATER LEVEL FORECASTING FOR FLOOD CONTROL: CASE STUDY ON KOYANA DAM", IJIERT - International Journal of Innovations in Engineering Research and Technology, ICCCES-16, ISSN : 2394-3696, Page No.