| Summary: | A flood is an extremely dangerous disaster that able wipe away an entire city, coastline, and rural area. The flood caused wide destroy to property and life that has the supreme corrosive force and can he highly damaging. This research explores the use of Artificial Neural Network (ANN) and Support Vector Machine (SVM) method to predict on the flood. Totally investigated 29 month data covering from January 2013 until May 2015 in Sungai Isap Kuantan, Pahang, Malaysia. Temperature, precipitation, dew point, humidity, sea level pressure, visibility, wind, and river level consider as a factor of a flood. This study proposes a comparison of prediction of SVM and ANN in flood. It is expected that SVM giving best result compare to ANN in term of accurate prediction with that prediction result is near to actual result.
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