Real Time Flood Prediction for Sungai Isap Residence Using Support Vector Machine - Khoo, Chun Keong; Mahfuzah, Mustafa; Ahmad Johari, Mohamad; M. H., Sulaiman (Astronautic Technology (M) Sdn. Bhd., 2015)
A flood is an extremely dangerous disaster that can wipe away an entire city, coastline, and rural area. The flood caused extensive damage to life and property that has great erosive power and can be extremely destructive. This research explores the use of Support Vector Machine (SVM) method to predict the flood in 2015. Total investigated 29 months data covering from January 2013 until May 2015 in the Sungai Isap Kuantan, Pahang, Malaysia. Rainfall, temperature and river level are considered as a factor of flood. From the experimental, it can be concluded the SVM technique is an efficient flood prediction. The proposed of SVM prediction models is for implemented in real-time flood warning system to let the residence to take action immediately.