OPERATIONAL HAZARD RISK ASSESSMENT USING BAYESIAN NETWORKS

Zoe Jing Yu Zhu, Yang Xiang, Ed McBean

Abstract

This research investigates a method for hazard identification of modern drinking water treatment technologies. Bayesian networks are applied to quantify risk assessment. Bayesian networks represent an important formalism for representation of, and inference with, uncertain knowledge in artificial intelligence. A physicochemical ultra filtration (UF) membrane train is expressed as a Bayesian network. They can be used in quantifying understanding of the hazards at the operational level of treatment plant that impact the risk of infection from pathogens. Once such a Bayesian network is established, the risk assessment can be performed automatically using algorithms developed in artificial intelligence which facilitates risk assessment of complex water treatment domains.

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Paper Citation


in Harvard Style

Zhu Z., Xiang Y. and McBean E. (2011). OPERATIONAL HAZARD RISK ASSESSMENT USING BAYESIAN NETWORKS . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-54-6, pages 135-139. DOI: 10.5220/0003430801350139


in Bibtex Style

@conference{iceis11,
author={Zoe Jing Yu Zhu and Yang Xiang and Ed McBean},
title={OPERATIONAL HAZARD RISK ASSESSMENT USING BAYESIAN NETWORKS},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2011},
pages={135-139},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003430801350139},
isbn={978-989-8425-54-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - OPERATIONAL HAZARD RISK ASSESSMENT USING BAYESIAN NETWORKS
SN - 978-989-8425-54-6
AU - Zhu Z.
AU - Xiang Y.
AU - McBean E.
PY - 2011
SP - 135
EP - 139
DO - 10.5220/0003430801350139