The Study Of Forest Fire Spread Model Based Cellular Automata And Simulation

Forest fires is a common natural disasters, forest fires bring a great deal of damage to the socio-economic and safety of the people. The forest fire is a kind of natural disasters that serious consequences and hard to control. When forest fire happened quickly and accurately, the predict and simulation of the spread and development of fire can in time provide scientific basis for decision-making for the deployment of putting out fire power, control the spread of fire extinguishing, and has great practical significance.Based on forest fire spread of its own characteristics, combined with cellular automata (CA) analysis and refine the effect the spread of forest fire key factors. Paper comprehensive analysis the forest factors of fires spread process, researches core influencing factors of the CA rules and focuses on the analysis of the changes of strength and the wind direction micro influence on fire spreading process. Based on the K-T modal which have a certain position in foreign, paper constructed a more micro and fitting with actual spreading process forest fire spread model.So as to better predict forest fire spread trends under different condition.With the development of CA research at present, CA in forest fires spread of prediction research is more and more widely, the thesis combines the modal, and according to the performance of CA strong ability of simulate complex system, Based on Matlab development platform, developing a based on cellular automata forest fire spreading prediction system. Emphasis simulates the experimental work on key influencing factors. Also, because the CA is a time, space, state discrete, spatial interactions and time causality for the local grid dynamic model. This system is simulated by using dynamic way, provide users with a friendly interface, and according to the simulation result to adjust and update related parameters. Finally get a better simulated forest fires spread of forecasting model. Through the contrastive analysis of the results, verify the model’s reliability and usability.