Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China). [PDF]
Wang Y, Sun D, Wen H, Zhang H, Zhang F.
europepmc +1 more source
"Ensembled transfer learning approach for error reduction in landslide susceptibility mapping of the data scare region". [PDF]
Singh A, Dhiman N, Niraj KC, Shukla DP.
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Research on the influence of different sampling resolution and spatial resolution in sampling strategy on landslide susceptibility mapping results. [PDF]
Yu X, Chen H.
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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. [PDF]
Nhu VH +15 more
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Improving pixel-based regional landslide susceptibility mapping
Xin Wei +6 more
semanticscholar +1 more source
Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping. [PDF]
Shirzadi A +13 more
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Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method. [PDF]
Arca D, Kutoğlu HŞ, Becek K.
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A heuristic approach to global landslide susceptibility mapping. [PDF]
Stanley T, Kirschbaum DB.
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A Novel Performance Assessment Approach Using Photogrammetric Techniques for Landslide Susceptibility Mapping with Logistic Regression, ANN and Random Forest. [PDF]
Sevgen E +3 more
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The Influence of Different Knowledge-Driven Methods on Landslide Susceptibility Mapping: A Case Study in the Changbai Mountain Area, Northeast China. [PDF]
Ma Z +6 more
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