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Forest Fire Tripping Probability Prediction System Based on Partial Mutual Information Method

机译:基于部分互信息方法的森林火灾跳闸概率预测系统

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摘要

High voltage transmission lines are mainly built in deep forests. However, forest fires have occurred frequently in recent years. At present, the power grids mainly monitor and warn forest fire, but they lack the longer time scale for the prediction of forest fire. Based on the partial mutual information method, the local fire risk level model is established, and then the forest fire tripping probability prediction system is established for the transmission lines of the power grid. On September 1, 2017 wildfires trip accident happened in some regions of Guangdong Province, and then the forest fire tripping probability in Guangdong Province is forecasted. The results show that the system can predict the accident area with a high probability of fire tripping about 1 day in advance, and the application of the system can provide longer time prediction information of forest fire tripping for the safe operation of power grid transmission lines.
机译:高压输电线主要建在森林深处。但是,近年来森林火灾频发。当前,电网主要监视和警告森林火灾,但是它们缺乏更长的时间来预测森林火灾。基于局部互信息法,建立局部火灾风险等级模型,然后建立电网输电线路森林火灾跳闸概率预测系统。 2017年9月1日,广东省部分地区发生森林火灾绊倒事故,然后预测了广东省森林火灾绊倒的可能性。结果表明,该系统可以提前1天左右预测出火灾事故的发生区域,并且该系统的应用可以为森林输电线路的安全运行提供更长的森林火灾跳闸时间预测信息。

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