Exploring Bayesian model averaging with multiple ANNs for meteorological drought forecasts

• Main Authors: Achite, Mohammed, Banadkooki, Fatemeh Barzegari, Ehteram, Mohammad, Bouharira, Abdelhak, Ahmed, Ali Najah, Elshafie, Ahmed
• Format: Article
• Published: Springer 2022
• Subjects: GE Environmental Sciences; TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/42077/

Forecasting drought is essential for water resource management when policymakers encounter a water shortage and high demand. This research utilizes the Bayesian averaging model (BMA) based on multiple hybrid artificial neural network models including ANN- water strider algorithm (WSA), ANN-particle...