基于粗糙集和ResNet34网络算法的森林火灾预测研究

Forest Fire Prediction Based on Rough Set and Resnet34 Network Algorithm

森林火灾是全世界面临的大问题,会对生态系统造成巨大的破坏,同时会威胁人类的生命财产安全。本文设计了一个有效的森林火灾预测算法,数据集采用Montesinho国家公园基本气象数据,建立粗糙集与ResNet网络算法建立森林火灾的成灾面积预测模型,对气温、相对湿度、风速和降水量等气象数据进行分析,并进行了森林火灾面积预测。研究结果显示,该算法能够较准确地预测规模较小且发生频繁的火灾受灾面积。

Forest fire is a major problem facing the whole world,which will cause great damage to the ecosystem and threaten the safety of human life and property.In this paper,an effective forest fire prediction algorithm is designed.Based on the basic meteorological data of montesinho National Park,rough set and RESNET network algorithm are used to establish the disaster area prediction model of forest fire.The meteorological data such as temperature,relative humidity,wind speed and precipitation are analyzed,and the forest fire area is predicted.The results show that the algorithm can accurately predict the fire disaster area with small scale and frequent occurrence.