Feature selection to diagnose a business crisis by using a real GA-based support vector machine: An empirical study

Expert Systems with Applications

Volumn 35, Issue 3, 2008, Pages 1145-1155

  Chen, Liang Hsuan ^a   Hsiao, Huey Der ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Business crisis; GA; Intellectual capital; SVM

Indexed keywords

ALGORITHMS; BIOELECTRIC PHENOMENA; GALLIUM; GENETIC ALGORITHMS; INFORMATION MANAGEMENT; KNOWLEDGE MANAGEMENT; LEARNING ALGORITHMS; MATHEMATICAL MODELS;

(E ,3E) PROCESS; BUSINESS DATA; BUSINESS MANAGERS; BUSINESS REPORTS; BUSINESS UNITS; ELSEVIER (CO); EMPIRICAL STUDIES; FEATURE SELECTION (FS); IN ORDER; INTELLECTUAL CAPITAL; OPTIMUM PARAMETERS; PREDICTION ACCURACY; REAL-VALUED GENETIC ALGORITHM; SELF-DIAGNOSIS; TRAINING PROCESSES;

SUPPORT VECTOR MACHINES;

EID: 44949091421     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.08.010     Document Type: Article

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