A novel hybrid intelligent approach for contractor default status prediction

Knowledge-Based Systems

Volumn 71, Issue , 2014, Pages 314-321

  Cheng, Min Yuan ^a,c   Hoang, Nhat Duc ^b   Limanto, Lisayuri ^a,c   Wu, Yu Wei ^a,c  

^a NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b DUY TAN UNIVERSITY   (Viet Nam)

^c NONE   (Taiwan)

Author keywords

Differential Evolution; Financial default prediction; Hybrid intelligence; Imbalanced classification; Least Squares Support Vector Machine

Indexed keywords

BENCHMARKING; CONSTRUCTION INDUSTRY; CONTRACTORS; EVOLUTIONARY ALGORITHMS; FORECASTING; OPTIMIZATION; SUPERVISED LEARNING;

CLASSIFICATION PERFORMANCE; DIFFERENTIAL EVOLUTION; DIFFERENTIAL EVOLUTION ALGORITHMS; HYBRID INTELLIGENCE; HYBRID INTELLIGENT APPROACH; IMBALANCED CLASSIFICATION; LEAST SQUARES SUPPORT VECTOR MACHINES; SYNTHETIC MINORITY OVER-SAMPLING TECHNIQUES;

SUPPORT VECTOR MACHINES;

EID: 85027938350     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2014.08.009     Document Type: Article

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