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A sequential method for the development of visual interactive meta-simulation models using neural networks

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  • R D Hurrion

    (University of Warwick)

Abstract

This paper proposes a practical and efficient method for the development of visual interactive meta-simulation models using neural networks. The method first uses a randomised simulation experimental design to obtain a set of results from a previously validated simulation model. The bootstrap technique is used on these results to generate a series of neural network models that are then trained using back propagation. The visual interactive meta-simulation model consists of the collective response from the trained neural network models. The accuracy of the meta-simulation model is assessed using the bootstrap technique and improved accuracy obtained by increasing the size of the randomised simulation experimental design set and re-training. This paper describes the approach, gives results for five example problems and suggests that the method is a practical extension to visual interactive simulation.

Suggested Citation

  • R D Hurrion, 2000. "A sequential method for the development of visual interactive meta-simulation models using neural networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(6), pages 712-719, June.
    • Handle: RePEc:pal:jorsoc:v:51:y:2000:i:6:d:10.1057_palgrave.jors.2600971
    DOI: 10.1057/palgrave.jors.2600971
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    Citations

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    Cited by:

    1. S Robinson & T Alifantis & J S Edwards & J Ladbrook & A Waller, 2005. "Knowledge-based improvement: simulation and artificial intelligence for identifying and improving human decision-making in an operations system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 912-921, August.
    2. S Robinson, 2005. "Discrete-event simulation: from the pioneers to the present, what next?," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 619-629, June.

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