Leak detection of pipeline: An integrated approach of rough set theory and artificial bee colony trained SVM

Expert Systems with Applications

Volumn 39, Issue 3, 2012, Pages 3071-3080

  Mandal, Santosh Kumar ^a   Chan, Felix T S ^b   Tiwari, M K ^c  

^a NATIONAL INSTITUTE OF FOUNDRY AND FORGE TECHNOLOGY   (India)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Artificial bee colony (ABC) algorithm; Leak detection; Rough set theory; Rule generation; Support vector machine (SVM)

Indexed keywords

ARTIFICIAL BEE COLONIES; ARTIFICIAL BEE COLONY (ABC) ALGORITHM; DECISION MAKING PROCESS; DETECTION AND LOCALIZATION; DETECTION SCHEME; ENHANCED PARTICLE SWARM OPTIMIZATION; EXPERIMENTAL DATA; FINANCIAL LOSS; FOOD SEARCHING; HONEY BEE; INTEGRATED APPROACH; PUBLIC HEALTH; RULE GENERATION; SUPPORT VECTOR; SVM CLASSIFIERS; SWARM INTELLIGENCE TECHNIQUES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELLULAR AUTOMATA; DECISION MAKING; LEAK DETECTION; LOSSES; PARTICLE SWARM OPTIMIZATION (PSO); SUPPORT VECTOR MACHINES;

ROUGH SET THEORY;

EID: 80255124873     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.08.170     Document Type: Article

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