Abstract In this article, the gully erosion susceptibility map (GESM) was developed for the Abdanan region, Ilam province, Iran using frequency ratio (FR), logistic regression (LR), an ensemble of radial basis function (RBF) and imperialist competitive algorithm (ICA) models. At first, 74 gully erosion locations have been recognized and then 52 (70%) cases had been regarded for training, while 22 (30%) cases validate the models. To model the GESM, 12 affecting factors on gully erosion were identified and prepared in a GIS environment, including altitude, slope angle, slope aspect, plan curvature, topographical wetness index (TWI), normalized differential vegetation index (NDVI), soil type, rainfall, distance to river, distance to road, lithology and land use in the study area. According to the results of LR model, slope aspect factor (2.439) is the most important and NDVI factor (–1.462) has the least importance on the occurrence of gully erosion. Also, the results of FR model show that MuPlaj class (FR = 2.5) of lithology factor is the most important in gully erosion. The ROC–AUC has been applied to confirm the accuracy of the models. The ROC–AUC results show efficiencies of 89.9%, 88.3% and 85.1% for RBF–ICA, LR and FR models, respectively.

中文翻译：

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使用人工智能和统计模型绘制沟壑侵蚀敏感性图

摘要 本文利用频率比（FR）、逻辑回归（LR）、径向基函数（RBF）和帝国主义竞争算法为伊朗伊拉姆省阿布达南地区开发了沟壑侵蚀敏感性图（GESM）。 (ICA) 模型。最初识别出 74 个冲沟侵蚀位置，然后考虑了 52 个（70%）案例进行训练，而 22 个（30%）案例验证了模型。为了模拟 GESM，在 GIS 环境中识别和准备了 12 个影响沟壑侵蚀的因素，包括海拔、坡角、坡向、平面曲率、地形湿度指数 (TWI)、归一化差异植被指数 (NDVI)、土壤类型、研究区的降雨量、与河流的距离、与道路的距离、岩性和土地利用。根据LR模型的结果，坡度纵横因子(2. 439) 是最重要的，NDVI 因子 (–1.462) 对冲沟侵蚀的发生最不重要。此外，FR模型的结果表明，岩性因子的MuPlaj类（FR = 2.5）在沟壑侵蚀中是最重要的。ROC-AUC 已被用于确认模型的准确性。ROC-AUC 结果显示 RBF-ICA、LR 和 FR 模型的效率分别为 89.9%、88.3% 和 85.1%。