东北地区典型细小死可燃物含水率预测及 5种模型比较

A comparison of five models in predicting surface dead fine fuel moisture content of typical forests in Northeast China

来源:中文会议(科协)
中文摘要英文摘要

[目的]细小可燃物含水率(FFMC)是火灾风险评估中的一个关键因素,它对林火的蔓延和发展有着重要的影响。目前,基于机器学习对其进行预测的方法很多,但很少有人关注它们与传统模型的比较,这导致了机器学习模型在 FFMC 预测中的应用存在一定的局限性。[方法]以半小时为步长,对中国东北地区 4种典型森林的FFMC进行长期野外观测,分析FFMC的动态变化及其驱动因素,建立5种不同的预测模型,并对其性能进行了比较。[结果]总体来看,半物理模型(Nelson…查看全部>>

[Objective]The spread and development of wildfires are deeply affected by the fine fuel moisture content(FFMC),which is a key factor in fire risk assessment.At present,there are many new prediction methods based on machine learning,but few people pay attention to their comparison with traditional models,which leads to some limitations in the application of machine learning in predicting FFMC.[Method]Therefore,we made long-term field observations of surface d…查看全部>>

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