FLOOD PREDICTION MODEL IN MALAYSIA: A REVIEW PAPER
Research Article
FLOOD PREDICTION MODEL IN MALAYSIA: A REVIEW PAPER
ABSTRACT
Flood is among the deadliest natural disaster in many countries, including Malaysia. Annually, flood happens in Malaysia at two different states, which is either in the form of a flash flood or seasonal flood. One way of understanding or forecasting incoming floods is by designing a reliable flood prediction model with an extended forecast period. Existing of the flood prediction model, the emergency response team has sufficient time to respond. This main paper contribution is to present a state-of-the-art flood prediction model. Researchers in Malaysia have been studying four significant forms of flood prediction models in recent years, which will be addressed in this paper too. These models are the Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA), machine learning, and Nonlinear Autoregressive Exogenous Artificial Neural Network (NARX). The accuracy and efficiency of the flood prediction model are essential, and these few factors need to be considered, Root Mean Square Error (RMSE), model best fit, and R-squared (R2 ). This paper thus proposes the most ambitious model of flood prediction to be used in Malaysia. This study can be used as a guideline to choose the proper flood prediction model for predicting floods.
WONG, W.,
&
SUBRAMANI, S.,
&
FEROZ, F.,
&
ROSE, L.,
(2020). FLOOD PREDICTION MODEL IN MALAYSIA: A REVIEW PAPER. International Journal of Technical and Natural Sciences, 1(2), 22-29. Arrival Date Posted By:https://ijtns.ibupress.com/articles/flood-prediction-model-in-malaysia-a-review-paper
