Landslide susceptibility mapping using state-of-the-art machine learning ensembles-Reference-Cited by-同舟云学术

Landslide susceptibility mapping using state-of-the-art machine learning ensembles

Published:2021-05-03 Issue: Volume: Page:1-26
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Pham Binh Thai¹^ORCID,Vu Vinh Duy²,Costache Romulus³,Phong Tran Van⁴,Ngo Trinh Quoc¹,Tran Trung-Hieu¹,Nguyen Huu Duy⁵,Amiri Mahdis⁶,Tan Mai Thanh⁴,Trinh Phan Trong⁴,Le Hiep Van¹,Prakash Indra⁷^ORCID

Affiliation:

1. University of Transport Technology, Hanoi, Vietnam

2. Institute of Marine Environment and Resources, Vietnam Academy of Science and Technology, Hanoi, Vietnam

3. Department of Civil Engineering, Transilvania University of Brasov, Brasov, Romania

4. Institute of Geological Sciences, Vietnam Academy of Sciences and Technology, Hanoi, Vietnam

5. Faculty of Geography, VNU University of Science, Vietnam National University, Hanoi, Vietnam

6. Department of Watershed & Arid Zone Management, Gorgan University of Agricultural Sciences & Natural Resources, Gorgan, Iran

7. DDG (R) Geological Survey of India, Gandhinagar, India

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2021.1914746

Reference136 articles.

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3. Landslide susceptibility mapping along road corridors in west Sulawesi using GIS-AHP models

4. Support Vector Machines for Landslide Susceptibility Mapping: The Staffora River Basin Case Study, Italy

5. Barakat N. 2010. Cascade generalization: Is SVMs' inductive bias useful? 2010 IEEE International Conference on Systems, Man and Cybernetics, October 10-13, 2010, Istanbul, Turkey.IEEE. p. 1393–1399

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