Landslide Dynamic Susceptibility Mapping Base on Machine Learning and the PS-InSAR Coupling Model

F Miao, Q Ruan, Y Wu, Z Qian, Z Kong, Z Qin - Remote Sensing, 2023 - mdpi.com
Complex and fragile geological conditions combined with periodic fluctuations in reservoir
water levels have led to frequent landslide disasters in the Three Gorges Reservoir area …

Machine learning embedded hybrid MCDM model to mitigate decision uncertainty in transport safety planning for OAS countries

W Zhou, H Feng, Z Guo, H Jia, Y Li, X Luo… - Socio-Economic …, 2024 - Elsevier
Providing defensible decisions is a prerequisite for methodologies of multi-criteria decision-
making (MCDM) activities, and this is especially true for socio-economic analysis in public …

Investigating machine learning and ensemble learning models in groundwater potential mapping in arid region: case study from Tan-Tan water-scarce region …

A Jari, EM Bachaoui, S Hajaj, A Khaddari… - Frontiers in …, 2023 - frontiersin.org
Groundwater resource management in arid regions has a critical importance for sustaining
human activities and ecological systems. Accurate mapping of groundwater potential plays a …

Estimating best nanomaterial for energy harvesting through reinforcement learning DQN coupled with fuzzy PROMETHEE under road-based conditions

SK Raju, GK Varadarajan, AH Alharbi, S Kannan… - Scientific Reports, 2024 - nature.com
Energy harvesters based on nanomaterials are getting more and more popular, but on their
way to commercial availability, some crucial issues still need to be solved. The objective of …

Landslide susceptibility zoning: integrating multiple Intelligent models with SHAP Analysis

I Prakash, DD Nguyen, NT Tuan, T Van Phong - Journal of Science and …, 2024 - jstt.vn
In this study, we aim to delineate landslide susceptibility zones within Dien Bien province,
Vietnam, leveraging the capabilities of various machine learning models including Light …

Predictive landslide susceptibility modeling in the southeastern hilly region of Bangladesh: application of machine learning algorithms in Khagrachari district

MM Hasan, SK Roy, MD Talha, MT Ferdous… - … Science and Pollution …, 2024 - Springer
Landslides pose a severe threat to people, buildings, and infrastructure. The rugged terrain
of the Chattogram Hill Tract region in southeastern Bangladesh frequently experiences …

[PDF][PDF] Hydric Erosion Mapping Enhancement in Korifla Sub-Watershed (Central Morocco)

F Eddefli, M Tayebi, S Hajaj, A Khaddari… - Journal of …, 2023 - intapi.sciendo.com
In recent years quantitative and qualitative methods integration has become common in
investigating and modeling hydric erosion. The present study focuses on using a synergistic …

Machine Learning Techniques for Multicriteria Decision-Making

W Shafik - Multi-Criteria Decision-Making and Optimum Design …, 2025 - taylorfrancis.com
In today's complex and data-driven world, decision-making often involves multiple conflicting
criteria, leading to the need for effective multicriteria decision-making (MCDM) techniques …

Assessing the Landslide Hazard in Västra Götaland, Sweden: A comparative analysis evaluating the accuracy of Spatial Multi Criteria Decision Analysis, Frequency …

H Dalhammer - 2024 - diva-portal.org
Due to global warming and changing weather conditions, landslide hazards are increasingly
threatening global populations. This is particularly concerning for Västra Götaland, Sweden …

Machine Learning Techniques for Landslide Susceptibility Mapping in Choman District, Iraq

K Chomani - EURASIAN JOURNAL OF SCIENCE AND …, 2024 - eajse.tiu.edu.iq
The geographic information system (GIS) and remote sensing techniques used in this study
with an integration of different machine learning techniques such as support vector machine …