Abstract
In order to better prevent fire and adapt to the change of the probability of extreme fire events in the next ten years, we establish an improved grey neural network prediction model. According to the collected data of climate characteristics, precipitation, temperature, humidity, wind speed and air pressure in southeastern Australia, they are quantified and processed as learning samples, and the improved grey neural network is used to predict the scale of wildfires in southeastern Australia. Through sensitivity analysis, the robustness of the model is guaranteed.
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