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Object-oriented Bayesian network for complex system risk assessment

Author

Listed:
  • Quan Liu
  • Ayeley Tchangani
  • François Pérès
  • Vicente Gonzalez-Prida

Abstract

In this article, we present a novel approach of modelling risk management process for complex systems. To overcome difficulties of modelling dynamic large-scale systems, the main idea is to split it into various structural homogeneous units. The object-oriented paradigm is used to this end but, unlike previous works, the proposed methodology allows variation in terms of internal parameters throughout the objects. This novel approach based on Bayesian network techniques is referred to as extended object-oriented Bayesian network. The main contribution of this article consists in establishing algorithms and methods on how to build and run such models. This article is an extension of a communication presented at AMEST by mainly developing a more realistic case study along with other improvements.

Suggested Citation

  • Quan Liu & Ayeley Tchangani & François Pérès & Vicente Gonzalez-Prida, 2018. "Object-oriented Bayesian network for complex system risk assessment," Journal of Risk and Reliability, , vol. 232(4), pages 340-351, August.
    • Handle: RePEc:sae:risrel:v:232:y:2018:i:4:p:340-351
    DOI: 10.1177/1748006X17753026
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    References listed on IDEAS

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    1. Paul Cilliers, 2001. "Boundaries, Hierarchies And Networks In Complex Systems," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 135-147.
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