A Contemporary Review on Drought Modeling Using Machine Learning Approaches

• Published in: Computer modeling in engineering & sciences Vol. 128; no. 2; pp. 447 - 487
• Main Authors: Sundararajan, Karpagam, Garg, Lalit, Srinivasan, Kathiravan, Bashir, Ali Kashif, Kaliappan, Jayakumar, Ganapathy, Ganapathy Pattukandan, Selvaraj, Senthil Kumaran, Meena
• Format: Journal Article
• Language: English
• Published: Henderson Tech Science Press 01.01.2021
• Subjects: Adaptive systems; Algorithms; Artificial intelligence; Artificial neural networks; Autoregressive models; Back propagation; Back propagation networks; Bayesian analysis; Decision trees; Deep learning; Drought; Drought Forecasting; Drought Indices; Dynamic Method; Evolutionary algorithms; Fuzzy Logic; Hybrid Method; Literature reviews; Machine Learning; Markov chains; Natural disasters; Natural resources; Performance measurement; Regression; Stochastic Models; Support vector machines; Weather forecasting

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 f...