Land subsidence susceptibility mapping: a new approach to improve decision stump classification (DSC) performance and combine it with four machine learning algorithms-Reference-Cited by-同舟云学术

Land subsidence susceptibility mapping: a new approach to improve decision stump classification (DSC) performance and combine it with four machine learning algorithms

Published:2024-02-01 Issue:10 Volume:31 Page:15443-15466
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Zhao Rui,Arabameri Alireza^ORCID,Santosh M.

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11356-024-32075-w.pdf

Reference141 articles.

1. Abelson M, Yechieli Y, Baer B, Lapid G, Behar N, Calvo R, Rosensaft M (2017) Natural versus human control on subsurface salt dissolution and development of thousands of sinkholes along the Dead Sea coast. J Geophys Res Earth Surf, 122 (6), https://doi.org/10.1002/2017JF004219

2. Abidin H, Andreas H, Gumilar I, Sidiq TP, Fukuda Y (2013) Land subsidence in coastal city of Semarang (Indonesia): characteristics, impacts and causes. Geomat Nat Haz Risk 4(3):226–240

3. Arabameri A, Pradhan B, Rezaei K, Yamani M, Pourghasemi HR, Lombardo L (2018) Spatial modelling of gully erosion using evidential belief function, logistic regression, and a new ensemble of evidential belief function–logistic regression algorithm. Land Degrad Dev 29(11):4035–4049

4. Arabameri A, Chen W, Blaschke T, Tiefenbacher JP, Pradhan B, Tien Bui D (2020) Gully head-cut distribution modeling using machine learning methods—a case study of NW Iran. Water 12(1):16

5. Arabameri, Saha S, Roy J, Tiefenbacher J, Cerda A, Biggs T, Pradhan B, ThaoThi Ngo P, Collin A (2020b) A novel ensemble computational intelligence approach for the spatial prediction of land subsidence susceptibility. Sci Total Environ 138595

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