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Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Drought Condition Derived using Rainfall Data

Rajesh Kumar Sharma1 , Mayank Rajput2 , Rahul Sharma3

Section:Research Paper, Product Type: Journal Paper
Volume-8 , Issue-6 , Page no. 122-125, Jun-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i6.122125

Online published on Jun 30, 2020

Copyright © Rajesh Kumar Sharma, Mayank Rajput, Rahul 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, Mayank Rajput, Rahul Sharma, “Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Drought Condition Derived using Rainfall Data,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.6, pp.122-125, 2020.

MLA Style Citation: Rajesh Kumar Sharma, Mayank Rajput, Rahul Sharma "Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Drought Condition Derived using Rainfall Data." International Journal of Computer Sciences and Engineering 8.6 (2020): 122-125.

APA Style Citation: Rajesh Kumar Sharma, Mayank Rajput, Rahul Sharma, (2020). Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Drought Condition Derived using Rainfall Data. International Journal of Computer Sciences and Engineering, 8(6), 122-125.

BibTex Style Citation:
@article{Sharma_2020,
author = {Rajesh Kumar Sharma, Mayank Rajput, Rahul Sharma},
title = {Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Drought Condition Derived using Rainfall Data},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2020},
volume = {8},
Issue = {6},
month = {6},
year = {2020},
issn = {2347-2693},
pages = {122-125},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5650},
doi = {https://doi.org/10.26438/ijcse/v8i6.122125}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i6.122125}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5650
TI - Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Drought Condition Derived using Rainfall Data
T2 - International Journal of Computer Sciences and Engineering
AU - Rajesh Kumar Sharma, Mayank Rajput, Rahul Sharma
PY - 2020
DA - 2020/06/30
PB - IJCSE, Indore, INDIA
SP - 122-125
IS - 6
VL - 8
SN - 2347-2693
ER -

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Abstract

This paper focuses on drought forecasting, using Artificial Neural Network (ANN) and predicts the values of drought condition derived using Rainfall data of Indore (M.P). We have used the Rainfall data as input data of ANN model for 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

Artificial Neural Networks (ANNs), SPI.

References

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