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Reseach Article

Article:Short term flood forecasting using General Recurrent neural network modeling a comparative study

by Rahul P. Deshmukh, A. A. Ghatol
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 8 - Number 12
Year of Publication: 2010
Authors: Rahul P. Deshmukh, A. A. Ghatol
10.5120/1259-1777

Rahul P. Deshmukh, A. A. Ghatol . Article:Short term flood forecasting using General Recurrent neural network modeling a comparative study. International Journal of Computer Applications. 8, 12 ( October 2010), 5-9. DOI=10.5120/1259-1777

@article{ 10.5120/1259-1777,
author = { Rahul P. Deshmukh, A. A. Ghatol },
title = { Article:Short term flood forecasting using General Recurrent neural network modeling a comparative study },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 8 },
number = { 12 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 5-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume8/number12/1259-1777/ },
doi = { 10.5120/1259-1777 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:57:09.520060+05:30
%A Rahul P. Deshmukh
%A A. A. Ghatol
%T Article:Short term flood forecasting using General Recurrent neural network modeling a comparative study
%J International Journal of Computer Applications
%@ 0975-8887
%V 8
%N 12
%P 5-9
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The artificial neural networks (ANNs) have been applied to various hydrologic problems recently. This research demonstrates dynamic neural approach by applying general recurrent neural network to rainfall-runoff modeling for the upper area of Wardha River in India. The model is developed by processing online data over time using dynamic modeling. Methodologies and techniques by applying different learning rule, activation function and input layer structure are presented in this paper and a comparison for the short term runoff prediction results between them is also conducted. The prediction results of the general recurrent neural network with Momentum learning rule and Tanh activation function with Axon as input layer structure indicates a satisfactory performance in the three hours ahead of time prediction. The conclusions also indicate that general recurrent neural network with Momentum learning rule and Tanh activation function with Axon as input layer structure is more versatile than other combinations for general recurrent neural network and can be considered as an alternate and practical tool for predicting short term flood flow.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial neural network Forecasting Rainfall Runoff Models