Puripat, C. and Pongpullponsak, A. / ICAS2014, May 21-24, 2014, Khon Kaen, Thailand Thailand river basin flood prediction using fuzzy rules Chalermchai Puripat 1 and Adisak Pongpullponsak 2* 1 Department of Mathematics, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand, poolsup973@gmail.com,chalermchai.pur@kbu.ac.th 2 Department of Mathematics, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand, adisak.pon@kmutt.ac.th Abstract This paper gives an approach to predict flood risk using fuzzy logic, fuzzy set and mandani inference. These methods provide a logical and systematic analysis of uncertainties, which can deal with many factor affect flooding in a relative simple and concrete way. However, A way of preventing flooding that is base a natural idea of Thai people because Thailand is in the tropical moisture. These causes were very flooding of the basin in Thailand. The aim of this paper is to perform demonstrate a simple risk system approach for this crisis. The disaster warning Thailand flood will be useful for people. This condition simulation is improved on qualitative planning issues like future flood prevention, flood early warning systems, preparedness, emergency response protocol during crisis, flooding mitigation systems arrangement and lessons learned. Rainfalls in the year have a different amount. Keywords: flood prediction, fuzzy logic, flood risk, *Corresponding Author E-mail Address: adisak.pon@kmutt.ac.th 1. Introduction The rainy Global warming affects climate change to each country around the globe, the significantly change in season like La Nina and El Nino[1] are followed with weather-related disasters and more degree of severity and also inevitably effecting to Thailand. For Thailand, The natural disasters from the report of the Department of Disaster Prevention and Mitigation, Ministry of Interior during 2009-2010 were floods, landslide, storms, droughts, colds, wildfires, earthquakes, tsunamis[2], diseases and pests. The most damages to agricultural sectors were floods and droughts. The consequence from flooding is household garbage, waste water, unemployment, and etc. The causes of flooding are amount and duration of rainfalls deposit on the ground and flow into canals and rivers, if volume of water is over the capacity of the rivers, water surpasses the river banks and deposits in the lower land for a long period of time. To predict flooding accurately, the rain fall, the depth of river, the contour, and the dam level are the input data to the fuzzy logic model. The result will reduce the risk from flood in the future. 2. Research Methodology 2.1 Fuzzy logic The basic concept in fuzzy logic Fuzzy logic is a tool to assist in decision making under uncertainty by allowing flexible. The main reason for using a simulation approach, the complexity of the human mind. Fuzzy logic is a special logical false (Boolean logic), a concept that has been expanded in terms of the actual (partial true) by the fact that in the period between the (completely true) to false. (completely false) the same logic is true and false only. Shown in Figure 2-1. Fig 2-1 Boolean logic and fuzzy logic A fuzzy(fuzziness) is called multi freelancers (multivalance) whose value is more than two values and differences with Britain that millions of France (bivalance) is a member of only two values, fuzzy. the sets (Fuzzy set) is a mathematical tool of the media. "The uncertainty (uncertainty)" is not only the second case by the theory of fuzzy sets to use meaningful variable (linguistic) rather than quantity. (quantitative) International Conference on Applied Statistics 2014 109