A cellular automaton integrating spatial case-based reasoning for predicting local landslide hazards-Reference-Cited by-同舟云学术

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A cellular automaton integrating spatial case-based reasoning for predicting local landslide hazards

Published:2023-11-15 Issue:1 Volume:38 Page:100-127
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Chen Jianhua¹,Xu Kaihang¹²,Zhao Zheng³,Gan Xianxia¹,Xie Huawei¹

Affiliation:

1. College of Geophysics, Chengdu University of Technology, Chengdu, China

2. Sichuan Engineering Technology Research Center of Geological Disaster Prevention, Chengdu, China

3. Institute of Geographic Sciences and Natural Resources Research, China Academy of Sciences, Beijing, China

Funder

Project of the Sichuan Science and Technology Program

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2023.2273877

Reference79 articles.

1. Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches

2. Factors Affecting Landslide Susceptibility Mapping: Assessing the Influence of Different Machine Learning Approaches, Sampling Strategies and Data Splitting

3. A comparison of slope units and grid cells as mapping units for landslide susceptibility assessment

4. A case-based reasoning system for supervised classification problems in the medical field

5. A review on fundamentals of case-based reasoning and its recent application in different domains

Cited by 3 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. Evaluating landslide susceptibility and landscape changes due to road expansion using optimized machine learning;Natural Hazards;2024-06-14

2. Landslide spatial prediction using cluster analysis;Gondwana Research;2024-06

3. Heterogeneous transfer learning considering feature representation and environmental consistency for landslide spatial prediction;GIScience & Remote Sensing;2024-05-09

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