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Rajesh Kumar Sharma1
Section:Research Paper, Product Type: Journal-Paper
Vol.9 ,
Issue.3 , pp.32-35, Jun-2021
Online published on Jun 30, 2021
Copyright © Rajesh Kumar Sharma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Rajesh Kumar Sharma, “Flood Forecasting, using Artificial Neural Network (ANN) and Predict Values of Flood condition Derived using River Water Level Data,” International Journal of Scientific Research in Computer Science and Engineering, Vol.9, Issue.3, pp.32-35, 2021.
MLA Style Citation: Rajesh Kumar Sharma "Flood Forecasting, using Artificial Neural Network (ANN) and Predict Values of Flood condition Derived using River Water Level Data." International Journal of Scientific Research in Computer Science and Engineering 9.3 (2021): 32-35.
APA Style Citation: Rajesh Kumar Sharma, (2021). Flood Forecasting, using Artificial Neural Network (ANN) and Predict Values of Flood condition Derived using River Water Level Data. International Journal of Scientific Research in Computer Science and Engineering, 9(3), 32-35.
BibTex Style Citation:
@article{Sharma_2021,
author = {Rajesh Kumar Sharma},
title = {Flood Forecasting, using Artificial Neural Network (ANN) and Predict Values of Flood condition Derived using River Water Level Data},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {6 2021},
volume = {9},
Issue = {3},
month = {6},
year = {2021},
issn = {2347-2693},
pages = {32-35},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=3389},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=3389
TI - Flood Forecasting, using Artificial Neural Network (ANN) and Predict Values of Flood condition Derived using River Water Level Data
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Rajesh Kumar Sharma
PY - 2021
DA - 2021/06/30
PB - IJCSE, Indore, INDIA
SP - 32-35
IS - 3
VL - 9
SN - 2347-2693
ER -
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Abstract :
This paper focuses on flood forecasting, using Artificial Neural Network (ANN) and predicts the values of flood condition derived using Narmada River Water level data of Hoshangabad (M.P). We have used the water level data as input data of ANN model for flood forecasting, and determine Standardized Water Level Index (SWLI). Artificial Neural networks operate on the principle of learning from a training set. There is a large variety of neural network models and learning procedures. Two classes of neural networks that are usually used for prediction applications are feed-forward networks and recurrent networks. They often train both of these networks using back-propagation algorithm.
Key-Words / Index Term :
Artificial Neural Networks (ANNs), SPI
References :
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[3]. Marzban, C. and Stumpf, G. J.: A neural network for tornado prediction based on Doppler radar-derived attributes. J. Appl. Meteor., 35, pp.617–626, 1996.
[4]. Mu¨ller, B., and Reinhardt, J.: Neural Networks: An Introduction, the Physics of Neural Networks Series, Springer-Verlag, 2, pp.266, 1991.
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