An artificial intelligence based framework to analyze the landside risk of a mountainous highway
Author:
Affiliation:
1. Department of Civil Engineering, National Institute of Technology, Hamirpur, India
2. Department of Natural Resource Management, Debre Berhan University, Debre Birhan, Ethiopia
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/10106049.2023.2186494
Reference59 articles.
1. Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria
2. Novel Credal Decision Tree-Based Ensemble Approaches for Predicting the Landslide Susceptibility
3. Assessment of Landslide Susceptibility Using Statistical- and Artificial Intelligence-based FR–RF Integrated Model and Multiresolution DEMs
4. Landslide Risk Assessment by using a New Combination Model based on a Fuzzy Inference System Method
5. Methodologies of Economic Measurement and Vulnerability Assessment for Application in Landslide Risk Analysis in a Highway Domain Strip: A Case Study in the Serra Pelada Region (Brazil)
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