Reliable prediction of rainfall extremes is vital for disaster management,
particularly in the context of increasing rainfall extremes due to global climate
change. Physical-empirical models have been developed in this study using three
widely used Machine Learning (ML) methods namely, Support Vector Machines
(SVM), Random Forests (RF), Bayesian Artificial Neural Networks (BANN) for the
prediction of rainfall and rainfall related extremes during Northeast Monsoon
(NEM) in Peninsular Malaysia from synoptic predictors.

Categories: Air, Hidrologi, Hujan
Tags: Artikel Jurnal, Data Penerbitan, Sulit