• DocumentCode
    2423952
  • Title

    An Improved Method for Project Duration Forecasting

  • Author

    Chen, X.X. ; Liu, L. ; Li, Y.

  • Author_Institution
    Sch. of Econ. & Manage., Beihang Univ., Beijing, China
  • fYear
    2010
  • fDate
    7-9 May 2010
  • Firstpage
    2644
  • Lastpage
    2647
  • Abstract
    There are many factors affect the accuracy of project duration forecasting, the lack of relative information and the complexity of the project are two major aspects. To overcome these constraints and establish a feasible forecasting model, this paper presents an improved method to forecast the project duration, which combines the earned schedule and artificial neural network. We adopt the artificial neural network because of its ability to model complex nonlinear relationship without a priori assumption of the nature of the relationship. The performance of the developed models was evaluated. The results show that the artificial neural network can improve the accuracy of the project duration forecasting significantly in terms of the error evaluation measurements.
  • Keywords
    forecasting theory; neural nets; project management; artificial neural network; project complexity; project duration forecasting; project management; relative information; Artificial neural networks; Forecasting; Indexes; Mathematical model; Neurons; Predictive models; Schedules; artificial neural network; earned schedule; project duration forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Business and E-Government (ICEE), 2010 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-0-7695-3997-3
  • Type

    conf

  • DOI
    10.1109/ICEE.2010.668
  • Filename
    5592044