目的探究评价指标的不同筛选方法和机器学习模型对崩岗易发性评价结果的影响。方法以石城县崩岗为例,通过不筛选、地理探测器(GD)筛选和多重共线性(VIF)筛选等方法构建评价指标体系,采用随机森林(RF)和多层感知机(MLP)模型,开展不同评价指标和评价模型对崩岗易发性的适宜性研究。结果1)GD筛选的崩岗易发性评价结果优于VIF筛选评价结果,采用指标累计贡献率q值为90%的GD筛选的结果与不筛选的结果基本相同;2)RF模型对崩岗易发性的预测效果优于MLP模型,其中不筛选、GD筛选 ...
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