A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses

Computers, Environment and Urban Systems

Volumn 34, Issue 3, 2010, Pages 216-235

  Pradhan, Biswajeet ^a   Lee, Saro ^b   Buchroithner, Manfred F ^a  

^a DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^b Korea Institute of Geosceince and Mineral Resources   (South Korea)

Author keywords

Cross application; Landslide; Malaysia; Neural network model; Susceptibility

Indexed keywords

AERIAL PHOTOGRAPHS; ANALYSIS RESULTS; AREA UNDER THE CURVES; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; BACK PROPAGATION NEURAL NETWORKS; CRITICAL ISSUES; CROSS-APPLICATION; FIELD SURVEYS; GEOINFORMATION TECHNOLOGIES; INVENTORY REPORT; LAND COVER; LANDSLIDE SUSCEPTIBILITY; MALAYSIA; NEURAL NETWORK MODEL; RELATIVE WEIGHTS; SPATIAL DATABASE; STUDY AREAS; SUSCEPTIBILITY MAPPING; SUSCEPTIBILITY MAPS; VERIFICATION RESULTS;

DATA FLOW ANALYSIS; LANDSLIDES; LOCATION; PHOTOGRAPHY;

NEURAL NETWORKS;

AERIAL PHOTOGRAPHY; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; FIELD SURVEY; GIS; LANDSLIDE; MAPPING METHOD; NUMERICAL MODEL; SPATIAL DATA;

MALAYSIA;

EID: 77952010906     PISSN: 01989715     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compenvurbsys.2009.12.004     Document Type: Article

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