Abstract
Precipitation is an important factor that predicts the occurrence of forest fires in the future. This study uses a time decay model to calculate the comprehensive precipitation index, which is an exponential weight decay model. This method can better represent the effect of precipitation in predicting the occurrence of forest fires. Besides, this study used the Support Vector Machine (SVM) regression model to construct a forest fire warning model. In the same area, using the comprehensive precipitation index compared with the average precipitation, the accuracy of the three forest areas in the test set has been improved by approximately 5%.
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