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Chang, Zhilu, Catani, Filippo, Huang, Faming, Liu, Gengzhe, Meena, Sansar Raj, Huang, Jinsong, Zhou, Chuangbing. Kexue Chubanshe,Science Press; 2022. Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors.
Huang, Faming, Xiong, Haowen, Yao, Chi, Catani, Filippo, Zhou, Chuangbing, Huang, Jinsong. Kexue Chubanshe,Science Press; 2023. Uncertainties of landslide susceptibility prediction considering different landslide types.
Chang, Zhilu, Huang, Jinsong, Huang, Faming, Bhuyan, Kushanav, Meena, Sansar Raj, Catani, Filippo. Elsevier; 2023. Uncertainty analysis of non-landslide sample selection in landslide susceptibility prediction using slope unit-based machine learning models.
Huang, Faming, Tao, Siyu, Li, Deying, Lian, Zhipeng, Catani, Filippo, Huang, Jinsong, Li, Kailong, Zhang, Chuhong. MDPI AG; 2022. Landslide Susceptibility Prediction Considering Neighborhood Characteristics of Landslide Spatial Datasets and Hydrological Slope Units Using Remote Sensing and GIS Technologies.
Chang, Zhilu, Huang, Faming, Huang, Jinsong, Jiang, Shui-Hua, Liu, Yuting, Meena, Sansar Raj, Catani, Filippo. Zhongguo Dizhi Daxue,China University of Geosciences; 2023. An updating of landslide susceptibility prediction from the perspective of space and time.
Huang, Faming, Xiong, Haowen, Chen, Shixuan, Lv, Zhitao, Huang, Jinsong, Chang, Zhilu, Catani, Filippo. China Coal Society; 2023. Slope stability prediction based on a long short-term memory neural network: comparisons with convolutional neural networks, support vector machines and random forest models.
Huang, Faming, Xiong, Haowen, Zhou, Xiaoting, Catani, Filippo, Huang, Jinsong. Springer; 2024. Modelling Uncertainties and Sensitivity Analysis of Landslide Susceptibility Prediction under Different Environmental Factor Connection Methods and Machine Learning Models.
Huang, Faming, Teng, Zuokui, Guo, Zizheng, Catani, Filippo, Huang, Jinsong. Elsevier; 2023. Uncertainties of landslide susceptibility prediction: Influences of different spatial resolutions, machine learning models and proportions of training and testing dataset.
Huang, Faming, Cao, Yu, Li, Wenbin, Catani, Filippo, Song, Guquan, Huang, Jinsong, Yu, Changshi. Zhongguo Meitan Xuehui / China Coal Society; 2024. Uncertainties of landslide susceptibility prediction: Influences of different study area scales and mapping unit scales.
Huang, Faming, Mao, Daxiong, Jiang, Bingchen, Li, Yijing, Jiang, Shui-Hua, Zhou, Chuangbing, Fan, Xuanmei, Zeng, Ziqiang, Catani, Filippo, Yu, Changshi, Chang, Zhilu, Huang, Jinsong. Zhongguo Dizhi Daxue,China University of Geosciences; 2024. Uncertainties in landslide susceptibility prediction modeling: A review on the incompleteness of landslide inventory and its influence rules.
Huang, Faming, Teng, Zuokui, Yao, Chi, Jiang, Shui-Hua, Catani, Filippo, Chen, Wei, Huang, Jinsong. Kexue Chubanshe; 2024. Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method.
Huang, Faming, Xiong, Haowen, Jiang, Shui-Hua, Yao, Chi, Fan, Xuanmei, Catani, Filippo, Chang, Zhilu, Zhou, Xiaoting, Huang, Jinsong, Liu, Keji. Elsevier; 2024. Modelling landslide susceptibility prediction: A review and construction of semi-supervised imbalanced theory.