The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Call for Papers
  • Proposals
  • Guest Editors

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Modular neural network approach for short term flood forecasting a comparative study

Author 1: Rahul P Deshmukh
Author 2: A. A. Ghatol

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2010.010514

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 1 Issue 5, 2010.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: The artificial neural networks (ANNs) have been applied to various hydrologic problems recently. This research demonstrates static neural approach by applying Modular feedforward 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 static modular neural network modeling. Methodologies and techniques for four models are presented in this paper and a comparison of the short term runoff prediction results between them is also conducted. The prediction results of the Modular feedforward neural network with model two indicate a satisfactory performance in the three hours ahead of time prediction. The conclusions also indicate that Modular feedforward neural network with model two is more versatile than other and can be considered as an alternate and practical tool for predicting short term flood flow.

Keywords: Artificial neural network, Forecasting, Rainfall, Runoff, Models.

Rahul P Deshmukh and A. A. Ghatol, “Modular neural network approach for short term flood forecasting a comparative study ” International Journal of Advanced Computer Science and Applications(IJACSA), 1(5), 2010. http://dx.doi.org/10.14569/IJACSA.2010.010514

@article{Deshmukh2010,
title = {Modular neural network approach for short term flood forecasting a comparative study },
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2010.010514},
url = {http://dx.doi.org/10.14569/IJACSA.2010.010514},
year = {2010},
publisher = {The Science and Information Organization},
volume = {1},
number = {5},
author = {Rahul P Deshmukh and A. A. Ghatol}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2022

3-4 March 2022

  • Virtual

Computing Conference 2022

14-15 July 2022

  • Hybrid / London, UK

IntelliSys 2022

1-2 September 2022

  • Hybrid / Amsterdam

Future Technologies Conference (FTC) 2022

20-21 October 2022

  • Hybrid / Vancouver
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org