Attribute selection using correlations and principal components for artificial neural networks employment for landslide susceptibility assessment
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Title
Attribute selection using correlations and principal components for artificial neural networks employment for landslide susceptibility assessment
Authors
Keywords
-
Journal
ENVIRONMENTAL MONITORING AND ASSESSMENT
Volume 192, Issue 2, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-01-21
DOI
10.1007/s10661-019-7968-0
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Note: Only part of the references are listed.- Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan
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- (2015) Jie Dou et al. NATURAL HAZARDS
- Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya
- (2013) Amar Deep Regmi et al. Arabian Journal of Geosciences
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- (2012) David Petley GEOLOGY
- Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models
- (2009) Biswajeet Pradhan et al. Environmental Earth Sciences
- Landslide susceptibility mapping using geological data, a DEM from ASTER images and an Artificial Neural Network (ANN)
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- Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning
- (2008) Robin Fell et al. ENGINEERING GEOLOGY
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