Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques-Reference-Cited by-同舟云学术

Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

Published:2017-11 Issue: Volume:297 Page:69-85
ISSN:0169-555X
Container-title:Geomorphology
language:en
Short-container-title:Geomorphology

Author:

Chen Wei,Pourghasemi Hamid Reza,Panahi Mahdi^ORCID,Kornejady Aiding^ORCID,Wang Jiale,Xie Xiaoshen,Cao Shubo

Funder

China Postdoctoral Science Foundation

Shaanxi Provincial Education Department

Open Fund of Shandong Provincial Key Laboratory of Depositional Mineralization & Sedimentary Minerals

Publisher

Elsevier BV

Subject

Earth-Surface Processes

Reference120 articles.

1. Theoretical foundations of the potential function method in pattern recognition learning;Ajzerman;Gms Medizinische Informatik Biometrie Und Epidemiologie,1964

2. Landslide hazard assessment: summary review and new perspectives;Aleotti;Bull. Eng. Geol. Environ.,1999

3. Intelligent landslide system based on discriminant analysis and cascade-forward back-propagation network;Alkhasawneh;Arabian Journal For Science & Engineering,2014

4. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan;Ayalew;Geomorphology,2005

5. Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan;Ayalew;Landslides,2004

Cited by 230 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Susceptibility evaluation of highway landslide disasters based on SBAS-InSAR: a case study of S211 highway in Lanping County;Natural Hazards;2024-09-12

2. Remote Sensing and GIS-Based Landslide Susceptibility Mapping in a Hilly District of Bangladesh: A Comparison of Different Geospatial Models;Journal of the Indian Society of Remote Sensing;2024-09-06

3. Integrated frequency ratio-analytical hierarchy and geospatial techniques-based earthquake risk assessment in mountainous cities: a case from the Northwestern Himalayas;Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards;2024-07-24

4. Effectiveness of hybrid ensemble machine learning models for landslide susceptibility analysis: Evidence from Shimla district of North-west Indian Himalayan region;Journal of Mountain Science;2024-07

5. Landslide Susceptibility Assessment by Machine Learning and Frequency Ratio Methods Using XRAIN Radar-Acquired Rainfall Data;Geosciences;2024-06-18