The invention relates to a forest fire prediction method and
system based on
artificial intelligence, and belongs to the technical field of fire prediction, and the
system comprises a data collection and fusion module which is used for obtaining multi-source
time sequence data of a target forest, the multi-source
time series data comprises meteorological data,
remote sensing image data, ground sensor data, topographic data and humanistic geographic data; the forest attribute analysis module judges whether the target forest belongs to a high-human-trace activity forest or a low-human-trace activity forest through a preset classification model; the self-adaptive
fire risk prediction engine is used for calculating a comprehensive
fire risk index of the target forest and generating a fire
occurrence probability space-
time distribution diagram; and the targeted remedial measure generation module is used for generating differentiated remedial measure plans matched with the forest attributes. According to the method, the human trace activity attributes of the forest can be accurately identified, the
fire risk factor weight is adaptively adjusted for forests with different attributes, and the accuracy of comprehensive
fire hazard index calculation is improved.