Forest fire prediction model based on Improved BP neural network

Konferenz: ICETIS 2022 - 7th International Conference on Electronic Technology and Information Science
21.01.2022 - 23.01.2022 in Harbin, China

Tagungsband: ICETIS 2022

Seiten: 5Sprache: EnglischTyp: PDF

Autoren:
Liu, Wenhao; Li, Pulin (Wuhan University of Technology, Wuhan, China)

Inhalt:
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.