Collapse susceptibility assessment using a support vector machine compared with back-propagation and radial basis function neural networks-Reference-Cited by-同舟云学术

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Collapse susceptibility assessment using a support vector machine compared with back-propagation and radial basis function neural networks

Published:2020-01-01 Issue:1 Volume:11 Page:510-534
ISSN:1947-5705
Container-title:Geomatics, Natural Hazards and Risk
language:en
Short-container-title:Geomatics, Natural Hazards and Risk

Author:

Li Yuanyao¹,Sheng Yifan¹,Chai Bo²,Zhang Wei¹,Zhang Taili³,Wang Jiajia⁴

Affiliation:

1. Institute of Geological Survey, China University of Geosciences, Wuhan, China

2. School of Environmental Studies, China University of Geosciences, Wuhan, China

3. Nanjing Center, China Geological Survey, Nanjing, China

4. School of Highway, Chang’an University, Xi’an, China

Funder

Project of ‘Geological hazards investigation in Feiyun river basin, Zhejiang province

‘Energy analysis of bedding rockslide developing from macroscopical deformation to failure

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/19475705.2020.1734101

Reference52 articles.

1. Landslide Susceptibility Prediction Based on Remote Sensing Images and GIS: Comparisons of Supervised and Unsupervised Machine Learning Models

2. GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naïve-Bayes tree, and alternating decision tree models

3. Support-vector networks

4. Automatic Case-Based Reasoning Approach for Landslide Detection: Integration of Object-Oriented Image Analysis and a Genetic Algorithm

5. Water Bodies’ Mapping from Sentinel-2 Imagery with Modified Normalized Difference Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band

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1. Rockfall susceptibility assessment in Kuandian County (Northeast China) by combining information content method and analytic hierarchy process;Bulletin of Engineering Geology and the Environment;2024-05-20

2. A support vector machine model of landslide susceptibility mapping based on hyperparameter optimization using the Bayesian algorithm: a case study of the highways in the southern Qinghai–Tibet Plateau;Natural Hazards;2024-05-15

3. An Integrated Model for Risk Assessment of Urban Road Collapse Based on China Accident Data;Sustainability;2024-03-01

4. Collapse Susceptibility Assessment in Taihe Town Based on Convolutional Neural Network and Information Value Method;Water;2024-02-28

5. Research on the influence of different sampling resolution and spatial resolution in sampling strategy on landslide susceptibility mapping results;Scientific Reports;2024-01-18

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