汤国安.地理信息系统教程[M].高等教育出版社,2019.

中国地震动参数区划图[S].2015.

严明,谢婉丽,何亚南,刘琦琦,何高锐,杨惠.基于极值降雨假设法的城镇地质灾害风险性评价耦合模型研究——以安康市岚皋县官元镇为例[J].灾害学,2023(04).

刘帅,朱杰勇,杨得虎,马博.不同降雨工况条件下的崩滑地质灾害危险性评价[J].地质科技通报,2024(02).

郭衍昊,窦杰,向子林,马豪,董傲男,罗万祺.基于优化负样本采样策略的梯度提升决策树与随机森林的汶川同震滑坡易发性评价[J].地质科技通报,2024(03).

李嘉昊,谢婉丽,严明,刘琦琦,何高锐.基于PCA与改进AHP-CRITIC法的地质灾害风险评价研究——以神木市为例[J].地球环境学报,2023(04).

田乃满,兰恒星,伍宇明,李郎平.人工神经网络和决策树模型在滑坡易发性分析中的性能对比[J].地球信息科学学报,2020(12).

罗路广,裴向军,黄润秋,裴钻,朱凌.GIS支持下CF与Logistic回归模型耦合的九寨沟景区滑坡易发性评价[J].工程地质学报,2021(02).

李苍柏,肖克炎,李楠,宋相龙,张帅,王凯,楚文楷,曹瑞.支持向量机、随机森林和人工神经网络机器学习算法在地球化学异常信息提取中的对比研究[J].地球学报,2020(02).

樊芷吟,苟晓峰,秦明月,范强,余建乐,赵建军.基于信息量模型与Logistic回归模型耦合的地质灾害易发性评价[J].工程地质学报,2018(02).

谢婉丽,滕宏泉,杜蕾,成天娥,杨惠,於红.大西安地区滑坡分类及其特征分析[J].地球环境学报,2018(01).

黄发明,殷坤龙,蒋水华,黄劲松,曹中山.基于聚类分析和支持向量机的滑坡易发性评价[J].岩石力学与工程学报,2018(01).

李郎平,兰恒星,郭长宝,张永双,李全文,伍宇明.基于改进频率比法的川藏铁路沿线及邻区地质灾害易发性分区评价[J].现代地质,2017(05).

赵欢,田伟平,齐洪亮,王福恒.陕西公路边坡灾害危险性分区研究[J].灾害学,2016(04).

滕宏泉,谢婉丽,盖海龙,葛瑞华,郭倩怡.分形分维理论在地质灾害发育及空间分布规律中的应用——以长安区滑坡、崩塌地质灾害为例[J].地质灾害与环境保护,2016(01).

谢婉丽,王延寿,马中豪,葛瑞华,王家鼎.黄土湿陷机理研究现状及发展趋势[J].现代地质,2015(02).

刘艺梁,殷坤龙,刘斌.逻辑回归和人工神经网络模型在滑坡灾害空间预测中的应用[J].水文地质工程地质,2010(05).

许冲,戴福初,姚鑫,赵洲,肖建章.基于GIS与确定性系数分析方法的汶川地震滑坡易发性评价[J].工程地质学报,2010(01).

邢秋菊,赵纯勇,高克昌,郭跃.基于GIS的滑坡危险性逻辑回归评价研究[J].地理与地理信息科学,2004(03).

马志江,陈汉林,杨树锋.基于支持向量机理论的滑坡灾害预测——以浙江庆元地区为例[J].浙江大学学报(理学版),2003(05).

Hao Zheng,Mingtao Ding.Spatiotemporal changes of landslide susceptibility in response to rainfall and its future prediction — A case study of Sichuan Province, China[J].Ecological Informatics,2024.

Biniyam Taye Alamrew,Tibebu Kassawmar,Likinaw Mengstie,Muralitharan Jothimani.Combined GIS, FR and AHP approaches to landslide susceptibility and risk zonation in the Baso Liben district, Northwestern Ethiopia[J].Quaternary Science Advances,2024.

Xiaoming Han,Xin Zhao,Yecheng Wu,Zhengwei Qu,Guofeng Li.A least squares–support vector machine for learning solution to multi-physical transient-state field coupled problems[J].Engineering Applications of Artificial Intelligence,2024.

Malik Talha Riaz,Muhammad Tayyib Riaz,Adnanul Rehman,Ahmed Ali Bindajam,Javed Mallick,Hazem Ghassan Abdo.An integrated approach of support vector machine (SVM) and weight of evidence (WOE) techniques to map groundwater potential and assess water quality[J].Scientific Reports,2024.

Kawawa Banda,Kevin Pietersen,Josefina Hamutoko,Thokozani Kanyerere,Muchaneta Munamati,Krasposy Kujinga,Imasiku Nyambe.Using a comparative of DRASTIC and Bayesian weights of evidence approach to assess transboundary aquifer vulnerability in a data scarcity region: Tuli-Karoo aquifer[J].Journal of Hydrology: Regional Studies,2024.

Lingli Zuo,Guohua Liu,Zhou Fang,Junyan Zhao,Jiajia Li,Shuyuan Zheng,Xukun Su.Assessing the destabilization risk of ecosystems dominated by carbon sequestration based on interpretable machine learning method[J].Ecological Indicators,2024.

Ruixiang Song, Shouzhi Wang, Lifang Song, Yi Rao, Heping Jiang.Landslide Susceptibility Assessment Based on Slope Unit and Information Value Method in Changbai Mountain District[J].Journal of Civil and Transportation Engineering,2024.

Bharat Prasad Bhandari,Subodh Dhakal,Ching Ying Tsou.Assessing the Prediction Accuracy of Frequency Ratio, Weight of Evidence, Shannon Entropy, and Information Value Methods for Landslide Susceptibility in the Siwalik Hills of Nepal[J].Sustainability,2024.

Melati Dian Nuraini,Umbara Raditya Panji,Astisiasari Astisiasari,Wisyanto Wisyanto,Trisnafiah Syakira,Trinugroho Trinugroho,Prawiradisastra Firman,Arifianti Yukni,Ramdhani Taufik Iqbal,Arifin Samsul,Anggreainy Maria Susan.A comparative evaluation of landslide susceptibility mapping using machine learning-based methods in Bogor area of Indonesia[J].Environmental Earth Sciences,2024.

Klai Adel,Katlane Rim,Haddad Romdhane,Rabia Mohamed Chedly.Landslide susceptibility mapping by frequency ratio and fuzzy logic approach: a case study of Mogods and Hedil (Northern Tunisia)[J].Applied Geomatics,2023.

Klai Adel,Katlane Rim,Haddad Romdhane,Rabia Mohamed Chedly.Landslide susceptibility mapping by frequency ratio and fuzzy logic approach: a case study of Mogods and Hedil (Northern Tunisia)[J].Applied Geomatics,2023.

Yuan Xinyue,Liu Chao,Nie Ruihua,Yang Zhengli,Li Weile,Dai Xiaoai,Cheng Junying,Zhang Junmin,Ma Lei,Fu Xiao,Tang Min,Xu Yina,Lu Heng.A Comparative Analysis of Certainty Factor-Based Machine Learning Methods for Collapse and Landslide Susceptibility Mapping in Wenchuan County, China[J].Remote Sensing,2022.

Chang Lili,Zhang Rui,Wang Chunsheng.Evaluation and Prediction of Landslide Susceptibility in Yichang Section of Yangtze River Basin Based on Integrated Deep Learning Algorithm[J].Remote Sensing,2022.

Lucchese Luísa Vieira,de Oliveira Guilherme Garcia,Pedrollo Olavo Correa.Investigation of the influence of nonoccurrence sampling on landslide susceptibility assessment using Artificial Neural Networks[J].Catena,2021.

Leo Breiman.Random Forests.[J].Machine Learning,2001.

Mohamed A. Shahin,Mark B. Jaksa,Holger R. Maier.Artificial neural network applications in geotechnical engineering[J].Australian Geomechanics,2001.

Wei Wang,Geng-Feng Wu,Xian-Yue Song.The application of neural networks to comprehensive prediction by seismology prediction method[J].Acta Seismologica Sinica,2000.

JoséI. Barredo,Annetty Benavides,Javier Hervás,Cees J. van Westen.Comparing heuristic landslide hazard assessment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain[J].International Journal of Applied Earth Observation and Geoinformation,2000.