A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India)

Environmental Modelling and Software

Volumn 84, Issue , 2016, Pages 240-250

  Pham, Binh Thai ^a,b   Pradhan, Biswajeet ^c   Tien Bui, Dieu ^d   Prakash, Indra ^e   Dholakia, M B ^a  

^a GUJARAT TECHNOLOGICAL UNIVERSITY   (India)

^b University of Transport Technology   (Viet Nam)

^c UNIVERSITY PUTRA MALAYSIA   (Malaysia)

^d UNIVERSITY OF SOUTH EASTERN NORWAY   (Norway)

^e Government of India)   (India)

Author keywords

India; Landslides susceptibility assessment; Machine learning; Uttarakhand

Indexed keywords

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; DISCRIMINANT ANALYSIS; LANDSLIDES; SUPPORT VECTOR MACHINES;

COMPARATIVE STUDIES; FISHER'S LINEAR DISCRIMINANT ANALYSIS; INDIA; LANDSLIDE SUSCEPTIBILITY ASSESSMENTS; LOGISTIC REGRESSIONS; MACHINE LEARNING METHODS; STATISTICAL INDICES; UTTARAKHAND;

LEARNING SYSTEMS;

ASSESSMENT METHOD; BAYESIAN ANALYSIS; COMPARATIVE STUDY; DISCRIMINANT ANALYSIS; INDEX METHOD; LANDSLIDE; MACHINE LEARNING; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; PROBABILITY DENSITY FUNCTION; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINE;

INDIA; UTTARAKHAND;

EID: 84989813944     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2016.07.005     Document Type: Article

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