AIMC Topic: Landslides

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Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms.

International journal of environmental research and public health Apr 16, 2020
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices, and can cause social upheaval and loss of life. As a result, many scientists study the phenomenon, and some of them have focused on producing landslide susce...
Logistic Models Support Vector Machine Neural Networks, Computer Algorithms Landslides Bayes Theorem Iran
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Attribute selection using correlations and principal components for artificial neural networks employment for landslide susceptibility assessment.

Environmental monitoring and assessment Jan 21, 2020
Landslide susceptibility maps can be developed with artificial neural networks (ANNs). In order to train our ANNs, a digital elevation model (DEM) and a scar map of one previous event were used. Eleven attributes are generated, possibly containing re...
Risk Landslides Algorithms Environmental Monitoring Neural Networks, Computer
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Multistage fuzzy comprehensive evaluation of landslide hazards based on a cloud model.

PloS one Nov 5, 2019
To accurately study the risk assessment of landslide disasters, firstly, the environmental conditions of induced landslide disasters are regarded as a fuzzy system, and the landslide risk factors in the multi-level analysis system are constructed to ...
Fuzzy Logic Landslides Risk Assessment China
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Mine landslide susceptibility assessment using IVM, ANN and SVM models considering the contribution of affecting factors.

PloS one Apr 11, 2019
The fragile ecological environment near mines provide advantageous conditions for the development of landslides. Mine landslide susceptibility mapping is of great importance for mine geo-environment control and restoration planning. In this paper, a ...
Neural Networks, Computer Risk Assessment Support Vector Machine Geographic Information Systems Landslides Environmental Monitoring
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Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China.

International journal of environmental research and public health Jan 28, 2019
The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural netw...
Disasters Landslides Satellite Imagery Predictive Value of Tests Area Under Curve Support Vector Machine Machine Learning Geographic Information Systems China Logistic Models
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An Ensemble Approach for Cognitive Fault Detection and Isolation in Sensor Networks.

International journal of neural systems Jun 26, 2016
Cognitive fault detection and diagnosis systems are systems able to provide timely information about possibly occurring faults without requiring any a priori knowledge about the process generating the data or the possible faults. This ability is cruc...
Datasets as Topic Landslides Neural Networks, Computer Algorithms Italy Computer Simulation Markov Chains Cognition
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Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Journal of environmental management Jul 1, 2025
Assessing multi-hazard susceptibility and understanding community insights are important for effective disaster risk management; however, limited research has been conducted to study these aspects together. This study uses a data-driven approach to a...
Pakistan Climate Change Geographic Information Systems Floods Surveys and Questionnaires Landslides Disaster Planning Perception
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Evaluation of landslide susceptibility based on SMOTE-Tomek sampling and machine learning algorithm.

PloS one Jan 1, 2025
Landslides are frequent and hazardous geological disasters, posing significant risks to human safety and infrastructure. Accurate assessments of landslide susceptibility are crucial for risk management and mitigation. However, geological surveys of l...
Machine Learning Humans China Landslides Algorithms
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Landslide susceptibility mapping using an entropy index-based negative sample selection strategy: A case study of Luolong county.

PloS one Jan 1, 2025
Landslides constitute a significant geological hazard in China, particularly in high-altitude regions like the Himalayas, where the challenging environmental conditions impede field surveys. This research utilizes the IOE model to refine non-landslid...
Models, Theoretical Tibet Machine Learning Satellite Imagery Environmental Monitoring China Humans Entropy Landslides
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