A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

Computers and Geosciences

Volumn 51, Issue , 2013, Pages 350-365

  Pradhan, Biswajeet ^a  

^a UNIVERSITY PUTRA MALAYSIA   (Malaysia)

Author keywords

Adaptive neuro fuzzy inference system (ANFIS); Decision tree (DT); GIS; Landslides; Malaysia; Remote sensing; Support vector machine (SVM)

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; AERIAL PHOTOGRAPHS; AREA UNDER THE ROC CURVE; COMPARATIVE STUDIES; DATA SETS; FIELD SURVEYS; GRID CELLS; INPUT PARAMETER; LANDSLIDE SUSCEPTIBILITY; LANDSLIDE SUSCEPTIBILITY MAPPING; MALAYSIA; NEURO-FUZZY MODEL; PREDICTION PERFORMANCE; PREDICTION RATE; PREDICTIVE ABILITIES; PROCESSED IMAGES; RECEIVER OPERATING CHARACTERISTICS; STUDY AREAS; THREE MODELS; TRAINING PHASE; VALIDATION RESULTS;

DECISION TREES; FORECASTING; FUZZY SYSTEMS; GEOGRAPHIC INFORMATION SYSTEMS; MAPPING; PIXELS; REMOTE SENSING; SUPPORT VECTOR MACHINES; TRACKING (POSITION);

LANDSLIDES;

AERIAL PHOTOGRAPH; ARTIFICIAL NEURAL NETWORK; COMPARATIVE STUDY; DECISION ANALYSIS; FUZZY MATHEMATICS; GIS; LANDSLIDE; MAPPING; NUMERICAL MODEL; PIXEL; REMOTE SENSING;

MALAYSIA;

EID: 84870298875     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2012.08.023     Document Type: Article

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