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Volumn 34, Issue 3, 2008, Pages 1974-1982

Decision support in construction equipment management using a nonparametric outlier mining algorithm

Author keywords

Algorithms; Computer analysis; Construction equipment; Data processing; Decision making

Indexed keywords

COMPUTER APPLICATIONS; CONSTRUCTION EQUIPMENT; DATA PROCESSING; DATA REDUCTION; DECISION MAKING; INDUSTRIAL MANAGEMENT;

EID: 37349022984     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.02.010     Document Type: Article
Times cited : (4)

References (13)
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    • AEM, Association of Equipment Manufacturers (2004). 2004-2005 Outlook for construction equipment business. Milwaukee, WI, USA.
  • 2
    • 0039253819 scopus 로고    scopus 로고
    • Breunig, M., Kriegel, H., Ng, R., & Sander, J. (2000). LOF: Identifying density-based local outliers. In Proceedings of the ACM SIGMOD 2000 international conference on management of data. Dalles, TX, USA.
  • 3
    • 33748956818 scopus 로고    scopus 로고
    • Fan, H., Kim, H., & AbouRizk, S. (2005). A non-parametric outlier mining algorithm for detecting anomalies in construction equipment database. In Proceedings of the sixth construction specialty conference (10p). CSCE, Toronto, May.
  • 4
    • 33745800069 scopus 로고    scopus 로고
    • Fan, H., Zaiane, O. R., Foss, A., & Wu, J. (2006). A nonparametric outlier detection for effectively discovering top-N outliers from engineering data. In Pacific-Asia conference on knowledge discovery and data mining (PAKDD) (pp. 557-66).
  • 5
    • 78149337520 scopus 로고    scopus 로고
    • Foss, A., & Zaiane, Z. (2002). A parameterless method for efficiently discovering clusters of arbitrary shape in large datasets. In Proceedings of the 2002 IEEE international conference on data mining (ICDM'02). Maebashi City, Japan.
  • 6
    • 0002954125 scopus 로고
    • Robust estimates, residuals, and outlier detection with multi-response data
    • Gnanadesikan R., and Kettenring J.R. Robust estimates, residuals, and outlier detection with multi-response data. Biometrics Journal 28 (1972) 81-124
    • (1972) Biometrics Journal , vol.28 , pp. 81-124
    • Gnanadesikan, R.1    Kettenring, J.R.2
  • 8
    • 37349004943 scopus 로고    scopus 로고
    • Knorr, E., & Ng, R. (1998). Algorithms for mining distance-based outliers in large datasets. In Proceedings of the 24th international conference on very large databases. New York, USA.
  • 9
    • 37349123659 scopus 로고    scopus 로고
    • Patak, Z. (1990). Robust principal component analysis via project pursuit. M.Sc. Thesis. Canada: University of British Columbia.
  • 10
    • 0035418979 scopus 로고    scopus 로고
    • Multivariate outlier detection and robust covariance matrix estimation
    • Pena D., and Prieto F. Multivariate outlier detection and robust covariance matrix estimation. Technometrics 43 3 (2001) 286-310
    • (2001) Technometrics , vol.43 , Issue.3 , pp. 286-310
    • Pena, D.1    Prieto, F.2
  • 12
    • 34249799115 scopus 로고    scopus 로고
    • Giants replace machines to control costs
    • Stewart L. Giants replace machines to control costs. Construction Equipment 102 3 (2000) 62
    • (2000) Construction Equipment , vol.102 , Issue.3 , pp. 62
    • Stewart, L.1
  • 13
    • 84945281435 scopus 로고    scopus 로고
    • Tang, J., Chen, Z., Fu, A., & Cheung, D. (2002). Enhancing effectiveness of outlier detections for low density patterns. In Proceedings of the sixth Pacific-Asia conference on advances in knowledge discovery and data mining (pp. 535-48). Taipei, Taiwan.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.