GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks

Environmental Earth Sciences

Volumn 75, Issue 14, 2016, Pages

  Tien Bui, Dieu ^a   Ho, Tien Chung ^b   Pradhan, Biswajeet ^c,g   Pham, Binh Thai ^d   Nhu, Viet Ha ^e   Revhaug, Inge ^f  

^a UNIVERSITY OF SOUTH EASTERN NORWAY   (Norway)

^b Vietnam Institute of Geosciences and Mineral Resources   (Viet Nam)

^c UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^d GUJARAT TECHNOLOGICAL UNIVERSITY   (India)

^e HANOI UNIVERSITY OF MINING AND GEOLOGY   (Viet Nam)

^f NORWEGIAN UNIVERSITY OF LIFE SCIENCES   (Norway)

^g Sejong University   (South Korea)

Author keywords

AdaBoost; Bagging; Functional trees; GIS; Landslide; MultiBoost; Vietnam

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; DECISION MAKING; DECISION TREES; FORESTRY; GEOGRAPHIC INFORMATION SYSTEMS; LAND USE; LANDSLIDES; LEARNING ALGORITHMS; LEARNING SYSTEMS; LITHOLOGY; NEURAL NETWORKS; RAIN; TREES (MATHEMATICS);

BAGGING; FUNCTIONAL TREES; LANDSLIDE SUSCEPTIBILITY ASSESSMENTS; MULTIBOOST; RAINFALL INDUCED LANDSLIDES; RECEIVER OPERATING CHARACTERISTICS; TOPOGRAPHIC WETNESS INDEX; VIET NAM;

ADAPTIVE BOOSTING;

ARTIFICIAL NEURAL NETWORK; DATA MINING; DECISION MAKING; DECISION SUPPORT SYSTEM; DISASTER MANAGEMENT; GIS; INVENTORY; LAND USE PLANNING; LANDSLIDE; MACHINE LEARNING; MODEL VALIDATION; PRECIPITATION INTENSITY;

VIET NAM;

EID: 84984580911     PISSN: 18666280     EISSN: 18666299     Source Type: Journal    
DOI: 10.1007/s12665-016-5919-4     Document Type: Article

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