• DocumentCode
    2321895
  • Title

    Business Process Engine Simulator

  • Author

    Pandey, Suraj ; Nepal, Surya ; Chen, Shiping

  • Author_Institution
    CSIRO, ICT Centre, Marsfield, NSW, Australia
  • fYear
    2012
  • fDate
    13-16 May 2012
  • Firstpage
    711
  • Lastpage
    713
  • Abstract
    Business process simulation is an effective approach to many organisations to understand the progress of processes over a period of time and predict future activities, which can then be given as a feedback to their customers and improve their overall productivity. In order to provide valuable information to both customers and system managers, the timings of business processes need to be forecast with high accuracy and efficiency. In particular, organisations require to study the process and event flows, recognize their patterns, and forecast the total time it would take for a workflow to complete. This paper proposes the architecture for business process simulation and describes its prototype implementation. It lists several prediction techniques that have been implemented as part of the prototype system. The paper also describes an artificial neural network model that could be used for predicting the completion time of business processes that are constrained by the availability of resources.
  • Keywords
    business data processing; forecasting theory; neural nets; artificial neural network model; business process engine simulator; event flow; pattern recognition; prediction technique; total time forecasting; Availability; Business; Engines; Hidden Markov models; Neural networks; Predictive models; Prototypes; Business Process Management; Prediction Techniques; Resource-constrained business processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2012 12th IEEE/ACM International Symposium on
  • Conference_Location
    Ottawa, ON
  • Print_ISBN
    978-1-4673-1395-7
  • Type

    conf

  • DOI
    10.1109/CCGrid.2012.130
  • Filename
    6217496