Subsidence risk assessment based on a novel hybrid form of a tree-based machine learning algorithm and an index model of vulnerability-Reference-Cited by-同舟云学术

Subsidence risk assessment based on a novel hybrid form of a tree-based machine learning algorithm and an index model of vulnerability

Published:2020-11-06 Issue: Volume: Page:1-29
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Mohebbi Tafreshi Ghazaleh¹^ORCID,Nakhaei Mohammad¹^ORCID,Lak Razyeh²^ORCID

Affiliation:

1. Department of Applied Geology, Faculty of Earth Sciences, Kharazmi University, Tehran, Iran

2. Research Institute for Earth Sciences, Geological Survey of Iran, Tehran, Iran

Funder

Institute for Earth Sciences

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1841835

Reference98 articles.

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4. Alimohammadi A. 2009. Provision and preparation of provincial planning plan, Studies of natural and environmental resources, Analysis of the status of geology, mineral resources and soil. Tehran Governorate, Iran: Deputy of Planning.

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