Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree
In this study, we introduced novel hybrid of evidence believe function (EBF) with logistic regression (EBF-LR) and logistic model tree (EBF-LMT) for landslide susceptibility modelling. Fourteen conditioning factors were selected, including slope aspect, elevation, slope angle, profile curvature, pla...
Saved in:
Main Authors: | Chen, Wei, Zhao, Xia, Shahabi, Himan, Shirzadi, Ataollah, Khosravi, Khabat, Chai, Huichan, Zhang, Shuai, Zhang, Lingyu, Ma, Jianquan, Chen, Yingtao, Wang, Xiaojing, Ahmad, Baharin, Li, Renwei |
---|---|
格式: | Article |
出版: |
Taylor and Francis Ltd.
2019
|
主題: | |
在線閱讀: | http://eprints.utm.my/id/eprint/88728/ http://dx.doi.org/10.1080/10106049.2019.1588393 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Uncertainties of prediction accuracy in shallow landslide modeling: sample size and raster resolution
由: Shirzadi, Ataollah, et al.
出版: (2019) -
Shallow landslide prediction using a novel hybrid functional machine learning algorithm
由: Dieu, Tien Bui, et al.
出版: (2019) -
Safety measures in construction logistics
由: Ratin, Nurul Fatimah
出版: (2019) -
The consumers’ convenience dimensions in performing food online purchase and its logistics level of service
由: Damerin, Noor Haslyana
出版: (2019) -
The consumers' convenience dimensions in performing food online purchase and its logistics level of service
由: Damerin, Noor Haslyana
出版: (2019)