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

Authors

  • Kumar Sharma R Department of Physics Unique College Bhopal (M.P), India
  • Rajput M Alpha College, NH 46 Bairagarh Khuman, Dist Sehore (M.P), India
  • Sharma R A-51 Exotica Villas Airport Road Bhopal (M.P), India

DOI:

https://doi.org/10.26438/ijcse/v8i1.191193

Keywords:

Data Source, Artificial Neural Network

Abstract

This paper focuses on drought forecasting, using Artificial Neural Network (ANN) and predicts the values of drought condition derived using Remote Sensing data of Indore (M.P). We have used the NDVI data as input data of ANN model for drought forecasting, and determine Standard Vegetation Index (SNDVI). 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.

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Published

2020-01-31
CITATION
DOI: 10.26438/ijcse/v8i1.191193
Published: 2020-01-31

How to Cite

[1]
R. Kumar Sharma, M. Rajput, and R. Sharma, “Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Drought Condition Derived using NDVI Data”, Int. J. Comp. Sci. Eng., vol. 8, no. 1, pp. 191–193, Jan. 2020.

Issue

Vol. 8 No. 1 (2020): IJCSE January Edition

Section

Research Article

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