Karpagam Sundararajan1, Lalit Garg2,*, Kathiravan Srinivasan4,*, Ali Kashif Bashir3, Jayakumar Kaliappan4, Ganapathy Pattukandan Ganapathy5, Senthil Kumaran Selvaraj6, T. Meena7
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 447-487, 2021, DOI:10.32604/cmes.2021.015528
- 22 July 2021
Abstract Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Its beginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughts in the last few decades. Predicting future droughts is vital for framing drought management plans to sustain natural resources. The data-driven modelling for forecasting the metrological time series prediction is becoming more powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques have demonstrated success in the drought prediction process and are becoming popular to More >
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