Haoyuan Hong
Orcid: 0000-0001-6224-069X
According to our database1,
Haoyuan Hong
authored at least 12 papers
between 2018 and 2024.
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Bibliography
2024
Landslide susceptibility assessment using locally weighted learning integrated with machine learning algorithms.
Expert Syst. Appl., March, 2024
2023
Applying a 1D Convolutional Neural Network in Flood Susceptibility Assessments - The Case of the Island of Euboea, Greece.
Remote. Sens., July, 2023
2022
Landslide Susceptibility Prediction Using Sparse Feature Extraction and Machine Learning Models Based on GIS and Remote Sensing.
IEEE Geosci. Remote. Sens. Lett., 2022
2021
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping.
Int. J. Geogr. Inf. Sci., 2021
2020
Potential of Ensemble Learning to Improve Tree-Based Classifiers for Landslide Susceptibility Mapping.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020
Uncertainties Analysis of Collapse Susceptibility Prediction Based on Remote Sensing and GIS: Influences of Different Data-Based Models and Connections between Collapses and Environmental Factors.
Remote. Sens., 2020
Using GIS, Remote Sensing, and Machine Learning to Highlight the Correlation between the Land-Use/Land-Cover Changes and Flash-Flood Potential.
Remote. Sens., 2020
Comparative study of landslide susceptibility mapping with different recurrent neural networks.
Comput. Geosci., 2020
Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping.
Comput. Geosci., 2020
2019
A Hybrid GIS Multi-Criteria Decision-Making Method for Flood Susceptibility Mapping at Shangyou, China.
Remote. Sens., 2019
2018
Landslide Detection and Susceptibility Mapping by AIRSAR Data Using Support Vector Machine and Index of Entropy Models in Cameron Highlands, Malaysia.
Remote. Sens., 2018
Landslide susceptibility assessment in the Anfu County, China: comparing different statistical and probabilistic models considering the new topo-hydrological factor (HAND).
Earth Sci. Informatics, 2018