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Hybrid artificial neural network and statistical model for forecasting project total duration in earned value management

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  • You Li
  • Lu Liu

Abstract

The paper proposes a new hybrid approach for forecasting project total durations in earned value management, which combines artificial neural network and random number simulation method to forecast the earned schedule indicator of each period one step further based on several nearest finished periods' status and then employs statistical method to estimate the project total duration and its intervals in each period of the project. Experiment results and test show our hybrid model outperforms the classic method of earned value management in both aspects of interval estimation and point estimation.

Suggested Citation

  • You Li & Lu Liu, 2012. "Hybrid artificial neural network and statistical model for forecasting project total duration in earned value management," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 10(3/4), pages 402-413.
    • Handle: RePEc:ids:ijnvor:v:10:y:2012:i:3/4:p:402-413
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    Cited by:

    1. Kwon, He-Boong, 2017. "Exploring the predictive potential of artificial neural networks in conjunction with DEA in railroad performance modeling," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 159-170.

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