Selecting forest fire spreading models based on the Fuzzy Data Mining technique

Forest fire spreading is of utmost complicated burning phenomenon and the scientific forest fire spreading model is crucial to predict forest fire behavior. According to the present situation of forest resources and forest fire prevention of Guangzhou City, based on the Fuzzy Data Mining (FDM) technique, thinking of the complicated environment, the suited forest fire spreading model can be selected to predict the behavior of forest fire. As to Guangzhou, the dominant influencing factors for forest fire behavior were assessed, including the water content of combustibles, burden quantity of combustibles, inflammability and slope. Therefore, the discovering and predicting functions of FDM are used in predicting the forest fire. According to the handy principle, three modes were discovered and the corresponding forest fire spreading model matches the certain style, which is induced from the fire data warehouse. Furthermore, so long as commander provides the real-time fire indices, the closely model can be ascertained by FDM. And the suited forest fire spreading model can be selected automatically to predict the forest fire behavior. By this means, the accuracy of predicting the behavior of forest fire can be improved.