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

Authors

  • Rajesh Kumar Sharma Department of Physics Unique College Bhopal (M.P), India

Keywords:

Data Source, Artificial Neural Network

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.

 

References

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Published

2020-12-31

How to Cite

[1]
R. K. Sharma, “Hydro Meteorological Drought Forecasting, using Artificial Neural Network (ANN) and Predict Values of Hydro Meteorological Drought Condition Derived using Rainfall Data”, Int. J. Sci. Res. Comp. Sci. Eng., vol. 8, no. 6, pp. 68–71, Dec. 2020.

Issue

Vol. 8 No. 6 (2020): December

Section

Research Article

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