Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS

Logistic Regression ◽

Frequency Ratio ◽

Network Models ◽

Neural Network Models ◽

Susceptibility Maps ◽

Artificial Neural Network Models ◽

Discussion on “Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS” by Choi et al. (2012), Engineering Geology, 124, 12–23

Engineering Geology ◽

10.1016/j.enggeo.2012.01.008 ◽

2012 ◽

Vol 129-130 ◽

pp. 104-105 ◽

Cited By ~ 7

Author(s):

C. Gokceoglu

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Engineering Geology ◽

Network Models ◽

Neural Network Models ◽

Susceptibility Maps ◽

Artificial Neural Network Models ◽

Comparison and evaluation of landslide susceptibility maps obtained from weight of evidence, logistic regression, and artificial neural network models

Natural Hazards ◽

10.1007/s11069-018-3299-7 ◽

2018 ◽

Vol 93 (1) ◽

pp. 249-274 ◽

Cited By ~ 31

Author(s):

Christos Polykretis ◽

Christos Chalkias

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Network Models ◽

Weight Of Evidence ◽

Neural Network Models ◽

Susceptibility Maps ◽

Artificial Neural Network Models ◽

Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models

Natural Hazards ◽

10.1007/s11069-013-0932-3 ◽

2013 ◽

Vol 71 (1) ◽

pp. 523-547 ◽

Cited By ~ 85

Author(s):

Vahid Nourani ◽

Biswajeet Pradhan ◽

Hamid Ghaffari ◽

Seyed Saber Sharifi

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Genetic Programming ◽

Frequency Ratio ◽

Network Models ◽

Landslide Susceptibility Mapping ◽

Neural Network Models ◽

Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea

Landslides ◽

10.1007/s10346-007-0088-x ◽

2007 ◽

Vol 4 (4) ◽

pp. 327-338 ◽

Cited By ~ 153

Author(s):

Saro Lee ◽

Joo-Hyung Ryu ◽

Ii-Soo Kim

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Likelihood Ratio ◽

Network Models ◽

Neural Network Models ◽

Susceptibility Analysis ◽

Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models

Environmental Earth Sciences ◽

10.1007/s12665-009-0245-8 ◽

2009 ◽

Vol 60 (5) ◽

pp. 1037-1054 ◽

Cited By ~ 357

Author(s):

Biswajeet Pradhan ◽

Saro Lee

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Frequency Ratio ◽

Network Models ◽

Landslide Hazard ◽

Neural Network Models ◽

Artificial Neural ◽

A comparative study of landslide susceptibility maps using logistic regression, frequency ratio, decision tree, weights of evidence and artificial neural network

Geosciences Journal ◽

10.1007/s12303-015-0026-1 ◽

2015 ◽

Vol 20 (1) ◽

pp. 117-136 ◽

Cited By ~ 79

Author(s):

Liang-Jie Wang ◽

Min Guo ◽

Kazuhide Sawada ◽

Jie Lin ◽

Jinchi Zhang

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Decision Tree ◽

Comparative Study ◽

Frequency Ratio ◽

Weights Of Evidence ◽

Susceptibility Maps ◽

Logistic regression and artificial neural network models for mapping of regional-scale landslide susceptibility in volcanic mountains of West Java (Indonesia)

10.1063/1.4947407 ◽

2016 ◽

Cited By ~ 4

Author(s):

Ngadisih ◽

Netra P. Bhandary ◽

Ryuichi Yatabe ◽

Ranjan K. Dahal

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Regional Scale ◽

Network Models ◽

Neural Network Models ◽

West Java ◽

Artificial Neural ◽

A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping

Geocarto International ◽

10.1080/10106049.2016.1140824 ◽

2016 ◽

Vol 32 (4) ◽

pp. 367-385 ◽

Cited By ~ 81

Author(s):

Wei Chen ◽

Hamid Reza Pourghasemi ◽

Zhou Zhao

Keyword(s):

Neural Network ◽

Logistic Regression ◽

Comparative Study ◽

Network Models ◽

Susceptibility Mapping ◽

Landslide Susceptibility Mapping ◽

Neural Network Models ◽

Development of a prediction model for pancreatic cancer in patients with type 2 diabetes using logistic regression and artificial neural network models

Cancer Management and Research ◽

10.2147/cmar.s180791 ◽

2018 ◽

Vol Volume 10 ◽

pp. 6317-6324 ◽

Cited By ~ 8

Author(s):

Meng Hsuen Hsieh ◽

Li-Min Sun ◽

Cheng-Li Lin ◽

Meng-Ju Hsieh ◽

Chung-Y. Hsu ◽

...

Keyword(s):

Neural Network ◽

Type 2 Diabetes ◽

Pancreatic Cancer ◽

Logistic Regression ◽

Prediction Model ◽

Network Models ◽

Neural Network Models ◽

Development, Validation and Comparison of Artificial Neural Network Models and Logistic Regression Models Predicting Survival of Unresectable Pancreatic Cancer

Frontiers in Bioengineering and Biotechnology ◽

10.3389/fbioe.2020.00196 ◽

2020 ◽

Vol 8 ◽

Author(s):

Zhou Tong ◽

Yu Liu ◽

Hongtao Ma ◽

Jindi Zhang ◽

Bo Lin ◽

...

Keyword(s):

Neural Network ◽

Pancreatic Cancer ◽

Logistic Regression ◽

Regression Models ◽

Network Models ◽

Unresectable Pancreatic Cancer ◽

Neural Network Models ◽

Logistic Regression Models ◽