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Volumn , Issue , 2006, Pages 1104-1113

Genetic algorithms for feature subset selection in equipment fault diagnosis

Author keywords

Fault diagnosis; Feature subset selection; Genetic algorithms

Indexed keywords

ASSET MANAGEMENT; FAILURE ANALYSIS; FAULT DETECTION; FEATURE EXTRACTION; FORECASTING; MACHINERY; REGRESSION ANALYSIS; SET THEORY; WEAR OF MATERIALS;

EID: 84868230890     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-1-84628-814-2_121     Document Type: Conference Paper
Times cited : (8)

References (17)
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  • 4
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  • 5
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    • Sielecki, W.1    Sklansky, J.2
  • 9
    • 0036739083 scopus 로고    scopus 로고
    • Genetic algorithm with fuzzy operators for feature subset selection IEICE Transactions on Fundamentals of Electronics
    • Chakraborty, B. (2002). Genetic algorithm with fuzzy operators for feature subset selection IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E85-A(9): 2089-2092.
    • (2002) Communications and Computer Sciences E85-A , Issue.9 , pp. 2089-2092
    • Chakraborty, B.1
  • 11
    • 27144489689 scopus 로고    scopus 로고
    • Balanced accuracy for feature subset selection with genetic algorithms
    • Sept. 2005, Edinburgh, Scotland, UK, IEEE
    • Peterson, M. R., M. L. Raymer, et al. (2005). Balanced accuracy for feature subset selection with genetic algorithms. The 2005 IEEE Congress on Evolutionary Computation, 2-5 Sept. 2005, Edinburgh, Scotland, UK, IEEE.
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    • Peterson, M.R.1    Raymer, M.L.2
  • 13
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    • Kuo, R.J.1    Cohen, P.H.2
  • 14
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    • Altintas, Y.1
  • 17
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.