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Volumn 112, Issue 1, 2012, Pages 4-23

Periodic performance prediction for real-time business process monitoring

Author keywords

Business activity monitoring; Business process management system; Business process re engineering; Imputation; Process analysis; Process monitoring; Real time monitoring; Support vector machine

Indexed keywords

BUSINESS ACTIVITY MONITORING; BUSINESS PROCESS MANAGEMENT SYSTEM; BUSINESS PROCESS RE-ENGINEERING; IMPUTATION; PROCESS ANALYSIS; REAL TIME MONITORING; SUPPORT VECTOR;

EID: 84862913173     PISSN: 02635577     EISSN: None     Source Type: Journal    
DOI: 10.1108/02635571211193617     Document Type: Article
Times cited : (40)

References (51)
  • 1
    • 0000225415 scopus 로고    scopus 로고
    • Implementing an industrial continuous improvement system: a knowledge management case study
    • Beckett, A.J., Wainwright, C.E.R. and Bance, D. (2000), “Implementing an industrial continuous improvement system: a knowledge management case study”, Industrial Management & Data Systems, Vol. 100 No. 7, pp. 330-8.
    • (2000) Industrial Management & Data Systems , vol.100 , Issue.7 , pp. 330-338
    • Beckett, A.J.1    Wainwright, C.E.R.2    Bance, D.3
  • 2
    • 30344472946 scopus 로고    scopus 로고
    • Understanding management data systems for enterprise performance management
    • Bose, R. (2006), “Understanding management data systems for enterprise performance management”, Industrial Management & Data Systems, Vol. 106 No. 1, pp. 43-59.
    • (2006) Industrial Management & Data Systems , vol.106 , Issue.1 , pp. 43-59
    • Bose, R.1
  • 3
    • 80052210374 scopus 로고    scopus 로고
    • How BAM can turn a business into a real-time enterprise
    • Gartner, Stamford, CT
    • Buytendijk, F. and Flint, D. (2002), “How BAM can turn a business into a real-time enterprise”, Gartner Research Note, AV-15-4650, Gartner, Stamford, CT.
    • (2002) Gartner Research Note, AV-15-4650
    • Buytendijk, F.1    Flint, D.2
  • 5
    • 77249166490 scopus 로고    scopus 로고
    • Integrating support vector machine and genetic algorithm to implement dynamic wafer quality prediction system
    • Chou, P.-H., Wu, M.-J. and Chen, K.-K. (2010), “Integrating support vector machine and genetic algorithm to implement dynamic wafer quality prediction system”, Expert Systems with Applications, Vol. 37 No. 6, pp. 4413-24.
    • (2010) Expert Systems with Applications , vol.37 , Issue.6 , pp. 4413-4424
    • Chou, P.-H.1    Wu, M.-J.2    Chen, K.-K.3
  • 7
    • 84992999384 scopus 로고
    • The new industrial engineering: information technology and business process redesign
    • Davenport, T.H. and Short, J.E. (1990), “The new industrial engineering: information technology and business process redesign”, Sloan Management Review, Vol. 31 No. 4, pp. 11-27.
    • (1990) Sloan Management Review , vol.31 , Issue.4 , pp. 11-27
    • Davenport, T.H.1    Short, J.E.2
  • 9
    • 0030613057 scopus 로고    scopus 로고
    • Development and testing of regeneration imputation models for forests in Minnesota
    • Ek, A.R., Robinson, A.P., Radtke, P.J. and Walters, D.K. (1997), “Development and testing of regeneration imputation models for forests in Minnesota”, Forest Ecology and Management, Vol. 94 Nos 1-3, pp. 129-40.
    • (1997) Forest Ecology and Management , vol.94 , Issue.1-3 , pp. 129-140
    • Ek, A.R.1    Robinson, A.P.2    Radtke, P.J.3    Walters, D.K.4
  • 10
    • 78649934709 scopus 로고    scopus 로고
    • University of California, School of Information and Computer Science, Irvine, CA
    • Frank, A and Asuncion, A. (2010), UCI Machine Learning Repository, University of California, School of Information and Computer Science, Irvine, CA, available at: http://archive.ics.uci.edu/ml.
    • (2010) UCI Machine Learning Repository
    • Frank, A.1    Asuncion, A.2
  • 16
    • 0001876297 scopus 로고
    • The treatment of missing survey data
    • Kalton, G. and Kasprzyk, D. (1986), “The treatment of missing survey data”, Survey Methodology, Vol. 12 No. 1, pp. 1-16.
    • (1986) Survey Methodology , vol.12 , Issue.1 , pp. 1-16
    • Kalton, G.1    Kasprzyk, D.2
  • 18
    • 80052247696 scopus 로고    scopus 로고
    • Real-time business process monitoring using formal concept analysis
    • Kang, B., Jung, J.-Y., Cho, N.W. and Kang, S.-H. (2011), “Real-time business process monitoring using formal concept analysis”, Industrial Management & Data Systems, Vol. 111 No. 5, pp. 652-74.
    • (2011) Industrial Management & Data Systems , vol.111 , Issue.5 , pp. 652-674
    • Kang, B.1    Jung, J.-Y.2    Cho, N.W.3    Kang, S.-H.4
  • 20
    • 84970352416 scopus 로고
    • The treatment of missing data in multivariate analysis
    • Kim, J. and Curry, J. (1977), “The treatment of missing data in multivariate analysis”, Sociological Methods Research, Vol. 6 No. 2, pp. 215-40.
    • (1977) Sociological Methods Research , vol.6 , Issue.2 , pp. 215-240
    • Kim, J.1    Curry, J.2
  • 21
    • 77956619667 scopus 로고    scopus 로고
    • A rule-based approach to proactive exception handling in business processes
    • Kim, K., Choi, I. and Park, C. (2010), “A rule-based approach to proactive exception handling in business processes”, Expert Systems with Applications, Vol. 38 No. 1, pp. 394-409.
    • (2010) Expert Systems with Applications , vol.38 , Issue.1 , pp. 394-409
    • Kim, K.1    Choi, I.2    Park, C.3
  • 22
    • 0030680974 scopus 로고    scopus 로고
    • Application of nearest-neighbor regression for generalizing sample tree information
    • Korhonen, K.T. and Kangas, A. (1997), “Application of nearest-neighbor regression for generalizing sample tree information”, Scandinavian Journal of Forest Research, Vol. 12 No. 1, pp. 97-101.
    • (1997) Scandinavian Journal of Forest Research , vol.12 , Issue.1 , pp. 97-101
    • Korhonen, K.T.1    Kangas, A.2
  • 23
    • 58349109662 scopus 로고    scopus 로고
    • A business process activity model and performance measurement using a time series ARIMA intervention analysis
    • Lam, C.Y., Ip, W.H. and Lau, C.W. (2009), “A business process activity model and performance measurement using a time series ARIMA intervention analysis”, Expert Systems with Applications, Vol. 36 No. 3, pp. 6986-94.
    • (2009) Expert Systems with Applications , vol.36 , Issue.3 , pp. 6986-6994
    • Lam, C.Y.1    Ip, W.H.2    Lau, C.W.3
  • 27
    • 34250765858 scopus 로고    scopus 로고
    • Business activity monitoring: calm before the storm
    • Gartner, Stamford, CT
    • McCoy, D.W. (2002), “Business activity monitoring: calm before the storm”, Gartner Research Note, LE-15-9727, Gartner, Stamford, CT.
    • (2002) Gartner Research Note, LE-15-9727
    • McCoy, D.W.1
  • 28
    • 68549085173 scopus 로고    scopus 로고
    • Inductive data mining based on genetic programming: automatic generation of decision trees from data for process historical data analysis
    • Ma, C.Y. and Wang, X.Z. (2009), “Inductive data mining based on genetic programming: automatic generation of decision trees from data for process historical data analysis”, Computers & Chemical Engineering, Vol. 33 No. 10, pp. 1602-16.
    • (2009) Computers & Chemical Engineering , vol.33 , Issue.10 , pp. 1602-1616
    • Ma, C.Y.1    Wang, X.Z.2
  • 29
    • 0032147985 scopus 로고    scopus 로고
    • Methods based on k-nearest neighbor regression in the prediction of basal area diameter distribution
    • Maltamo, M. and Kangas, A. (1998), “Methods based on k-nearest neighbor regression in the prediction of basal area diameter distribution”, Canadian Journal of Forest Research, Vol. 28 No. 8, pp. 1107-15.
    • (1998) Canadian Journal of Forest Research , vol.28 , Issue.8 , pp. 1107-1115
    • Maltamo, M.1    Kangas, A.2
  • 30
    • 0000256443 scopus 로고
    • Most similar neighbor: an improved sampling inference procedure for natural resource planning
    • Moeur, M. and Stage, A.R. (1995), “Most similar neighbor: an improved sampling inference procedure for natural resource planning”, Forest Science, Vol. 41 No. 2, pp. 337-59.
    • (1995) Forest Science , vol.41 , Issue.2 , pp. 337-359
    • Moeur, M.1    Stage, A.R.2
  • 31
    • 0141525951 scopus 로고    scopus 로고
    • Workflow-based process controlling – or: what you can measure you can control
    • Future Strategies, Wallsend
    • Muehlen, M. (2001), “Workflow-based process controlling – or: what you can measure you can control”, Workflow Handbook, Future Strategies, Wallsend, pp. 61-77.
    • (2001) Workflow Handbook , pp. 61-77
    • Muehlen, M.1
  • 35
    • 44149094285 scopus 로고    scopus 로고
    • Stochastic optimization modeling and quantitative project management
    • Rao, U.S., Kestur, S. and Pradhan, C. (2008), “Stochastic optimization modeling and quantitative project management”, IEEE Software, Vol. 25 No. 3, pp. 29-36.
    • (2008) IEEE Software , vol.25 , Issue.3 , pp. 29-36
    • Rao, U.S.1    Kestur, S.2    Pradhan, C.3
  • 38
    • 33746134593 scopus 로고    scopus 로고
    • A BPM taxonomy: creating clarity in a confusing market
    • Gartner, Stamford, CT
    • Sinur, J. and Bell, T. (2003), “A BPM taxonomy: creating clarity in a confusing market”, Gartner Research Note, T-18-9669, Gartner, Stamford, CT.
    • (2003) Gartner Research Note, T-18-9669
    • Sinur, J.1    Bell, T.2
  • 40
    • 0032594959 scopus 로고    scopus 로고
    • An overview of statistical learning theory
    • Vapnik, V. (1999), “An overview of statistical learning theory”, IEEE Transactions on Neural Networks, Vol. 10 No. 5, pp. 988-99.
    • (1999) IEEE Transactions on Neural Networks , vol.10 , Issue.5 , pp. 988-999
    • Vapnik, V.1
  • 41
    • 0000086228 scopus 로고
    • Moments and distributions of estimates of population parameters from fragments samples
    • Walks, S. (1932), “Moments and distributions of estimates of population parameters from fragments samples”, Annals of Mathematical Statistics, Vol. 3, pp. 163-203.
    • (1932) Annals of Mathematical Statistics , vol.3 , pp. 163-203
    • Walks, S.1
  • 42
    • 22344456074 scopus 로고    scopus 로고
    • Robust multi-scale principal components analysis with applications to process monitoring
    • Wang, D. and Romagnoli, J.A. (2005), “Robust multi-scale principal components analysis with applications to process monitoring”, Journal of Process Control, Vol. 15 No. 8, pp. 869-82.
    • (2005) Journal of Process Control , vol.15 , Issue.8 , pp. 869-882
    • Wang, D.1    Romagnoli, J.A.2
  • 43
    • 44149115746 scopus 로고    scopus 로고
    • Point argument: applying SPC to software development: where and why
    • Weller, E. and Card, D. (2008), “Point argument: applying SPC to software development: where and why”, IEEE Software, Vol. 25 No. 3, pp. 48-51.
    • (2008) IEEE Software , vol.25 , Issue.3 , pp. 48-51
    • Weller, E.1    Card, D.2
  • 47
    • 34249661124 scopus 로고    scopus 로고
    • Support vector machine in machine condition monitoring and fault diagnosis
    • Widodo, A. and Yang, B.-S. (2007), “Support vector machine in machine condition monitoring and fault diagnosis”, Mechanical Systems and Signal Processing, Vol. 21 No. 6, pp. 2560-74.
    • (2007) Mechanical Systems and Signal Processing , vol.21 , Issue.6 , pp. 2560-2574
    • Widodo, A.1    Yang, B.-S.2
  • 48
    • 78049527731 scopus 로고    scopus 로고
    • Hybrid fuzzy support vector classifier machine and modified genetic algorithm for automatic car assembly fault diagnosis
    • Wu, Q. (2011), “Hybrid fuzzy support vector classifier machine and modified genetic algorithm for automatic car assembly fault diagnosis”, Expert Systems with Applications, Vol. 38 No. 3, pp. 1457-63.
    • (2011) Expert Systems with Applications , vol.38 , Issue.3 , pp. 1457-1463
    • Wu, Q.1
  • 49
    • 71749091806 scopus 로고    scopus 로고
    • A hybrid approach of DEA, rough set and support vector machines for business failure prediction
    • Yeh, C.-C., Chi, D.-J. and Hsu, M.-F. (2010), “A hybrid approach of DEA, rough set and support vector machines for business failure prediction”, Expert Systems with Applications, Vol. 37 No. 2, pp. 1535-41.
    • (2010) Expert Systems with Applications , vol.37 , Issue.2 , pp. 1535-1541
    • Yeh, C.-C.1    Chi, D.-J.2    Hsu, M.-F.3
  • 50
    • 0032295215 scopus 로고    scopus 로고
    • Modeling of strength of high performance concrete using artificial neural networks
    • Yeh, I.-C. (1998), “Modeling of strength of high performance concrete using artificial neural networks”, Cement and Concrete Research, Vol. 28 No. 12, pp. 1797-808.
    • (1998) Cement and Concrete Research , vol.28 , Issue.12 , pp. 1797-1808
    • Yeh, I.-C.1


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