Predicting the Droughts Using Artificial Neural Networks – A Case Study

Characterizing drought prediction with deep learning: A literature review

“…SPEI is the most commonly used set for prediction as it establishes a relationship between precipitation and evapotranspiration [ 4 ]. SPEI has been used in drought prediction with AI in various regions, including China [ [53] , [54] , [55] , [56] , [57] , [58] , [59] , [60] , [61] , [62] , [63] ], Australia [ 38 , 41 , 42 ], and Iran [ [9] , [18] , [64] , [65] ]. These regions are known for their hot and arid weather conditions.…”

“…It is worth mentioning that the World Meteorological Organization (WMO) recommends using SPI to describe the phenomenon [ 66 ]. This index has been utilized to forecast drought using AI tools in different parts of the world, such as Turkey [ 67 ], Nigeria [ 68 ], India [ 12 , [32] , [57] ], Indonesia [ 69 ], and Mexico [ 70 ].…”