Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models

• Main Authors: Elbeltagi A., Pande C.B., Kumar M., Tolche A.D., Singh S.K., Kumar A., Vishwakarma D.K.
• Other Authors: 57204724397
• Format: Article
• Published: Springer Science and Business Media Deutschland GmbH 2024
• Subjects: Drought; Machine learning; Random forest (RF); Standardized precipitation index (SPI); Algorithms; Droughts; Ecosystem; India; Random Forest; Maharashtra; drought; Gaussian method; geographical region; machine learning; meteorology; precipitation (climatology); regression analysis; algorithm; ecosystem; random forest
• Institution: Universiti Tenaga Nasional

Agriculture, meteorological, and hydrological drought is a natural hazard which affects ecosystems in the central India of Maharashtra state. Due to limited historical data for drought monitoring and forecasting available in the central India of Maharashtra state, implementing machine learning (ML)...