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Rajesh Kumar Sharma1
Section:Research Paper, Product Type: Journal-Paper
Vol.8 ,
Issue.6 , pp.68-71, Dec-2020
Online published on Dec 31, 2020
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, “Hydro Meteorological Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Hydro Meteorological Drought Condition Derived using Rainfall Data,” International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.6, pp.68-71, 2020.
MLA Style Citation: Rajesh Kumar Sharma "Hydro Meteorological Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Hydro Meteorological Drought Condition Derived using Rainfall Data." International Journal of Scientific Research in Computer Science and Engineering 8.6 (2020): 68-71.
APA Style Citation: Rajesh Kumar Sharma, (2020). Hydro Meteorological Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Hydro Meteorological Drought Condition Derived using Rainfall Data. International Journal of Scientific Research in Computer Science and Engineering, 8(6), 68-71.
BibTex Style Citation:
@article{Sharma_2020,
author = {Rajesh Kumar Sharma},
title = {Hydro Meteorological Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Hydro Meteorological Drought Condition Derived using Rainfall Data},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {12 2020},
volume = {8},
Issue = {6},
month = {12},
year = {2020},
issn = {2347-2693},
pages = {68-71},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=3388},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=3388
TI - Hydro Meteorological Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Hydro Meteorological Drought Condition Derived using Rainfall Data
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Rajesh Kumar Sharma
PY - 2020
DA - 2020/12/31
PB - IJCSE, Indore, INDIA
SP - 68-71
IS - 6
VL - 8
SN - 2347-2693
ER -
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Abstract :
This paper focuses on Hydro Metrological Drought Forecasting, using Artificial Neural Network (ANN) and predicts the values of Hydro Meteorological Drought condition derived using Rainfall data of Bhopal (M.P). We have used the Rainfall data as input data of ANN model for Hydro Meteorological Drought forecasting, and determine Standardized Precipitation Index (SPI). 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 :
Data Source, Artificial Neural Network
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.
[5]. McKee, T. B., Doesken, N. J. and Kleist J.: The relation of drought frequency and duration to time scales, Proceedings of the Eighth Conference on Applied Climatology, American Meteorological Society, Boston. pp.179–184, 1993.
[6]. McKee, T. B., Doesken, N. J. and Kleist, J.: Drought monitoring with multiple time scales. Proceedings of the Ninth Conference on Applied Climatology; American Meteorological Society, Boston. pp.233–236, 1995.
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