Forest fire prediction model based on Improved BP neural network

Forest fire is destructive and difficult to deal with. To effectively prevent forest fire, it is necessary to establish a reliable prediction model. In this paper, based on BP neural network, a prediction model of the number of forest disasters in Alberta Province is established by selecting more appropriate meteorological conditions as characteristic factors and optimizing the structure of the neural network, so as to better predict the occurrence of forest fires and reduce the risk of fire.