Forest Fire Evolution Prediction Using a Hybrid Intelligent System

Forest fires represent a quite complex environment and an accurate prediction of the fires generated is crucial when trying to react quickly and effectively in such a critical situation. In this study, an hybrid system is applied to predict the evolution of forest fires. The Case-Based Reasoning methodology combined with a summarization of SOM ensembles algorithm has been used to face this problem. The CBR methodology is used as the solution generator in the system, reusing past solutions given to past problems to generate new solutions to new problems by adapting those past solutions to the new situations to face. On the other hand, a new summarization algorithm (WeVoS-SOM) is used to organize the stored information to make it easier to retrieve the most useful information from the case base. The developed system has been checked with forest fires historical and experimental data. The WeVoS-CBR system presented here has successfully predicted the evolution of the forest fires in terms of probability of finding fires in a certain area.