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PREDICTING BURNED AREAS OF FOREST FIRES: AN ARTIFICIAL INTELLIGENCE APPROACH

Tanuja Mote, Aarti Singh, Menka Prasad, Poonamdevi Kalwar


Predicting Burned Areas Of Forest Fires: An Artificial Intelligence Approach” is a software application for predicting the propagation of forest fire to identify the burned area during the event of fire. Forest fires are a major environmental issue, creating economical and ecological damage while endangering human lives. It importantly influences our environment and lives. Predicting forest fire propagation is a crucial issue when fighting these hazards as efficiently as possible. Fast detection is a key element for controlling such phenomenon. Powerful computational tools are needed to predict the amount of area that will be burned during a forest fire. There is a need of a system for predicting the area that may be affected in a forest fire event. Different techniques are available in literature to solve such crucial issue including Mathematical model, FWI calculator. Such models require a set of input parameters and that should be precise and the calculations are based on mathematical formulas which require more time and unable to provide accurate result. We proposed an intelligent system based on genetic programming for the prediction of burned areas, using data like relative humidity, temperature, wind, speed, slope, drought factor etc parameters which are possibly easily known and collectable to any forest officer.