Research on risk fuzzy comprehensive evaluation for construction engineering projects based on AHM

Li, Gaoyang, Packianather, Michael ORCID: https://orcid.org/0000-0002-9436-8206, He, Chunbao and Liu, Mingguang 2018. Research on risk fuzzy comprehensive evaluation for construction engineering projects based on AHM. Presented at: 2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), NIngbo, China, 19-21 November 2017. 2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM). 2017 IEEE INTERNATIONAL CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS (CIS) AND IEEE CONFERENCE ON ROBOTICS, AUTOMATION AND MECHATRONICS (RAM). IEEE, pp. 605-608. 10.1109/ICCIS.2017.8274846

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Abstract

It is necessary for investors and construction enterprises to evaluate project risk objectively in order to manage and control project risk effectively and further reduce economic losses. This paper firstly builds projects risk evaluation index system including social risks, economic risks, technical risks, manage risks and equipment risks based on the characteristics of the project risk assessment so that projects risk qualitative evaluation is transformed into a quantitative evaluation problem; Secondly, using each advantages of the Analytic Hierarchical Model (AHM) and Fuzzy Comprehensive Evaluation, the index weights are decided by AHM and the uncertainty of risk can be quantified and measured by the fuzzy comprehensive evaluation, then the model of the project risk fuzzy comprehensive evaluation is built. As a result, the fuzzy comprehensive evaluation method is suitable for engineering project risk evaluation. Lastly, a case analysis on the data obtained from experts indicates that it is feasible for the combination of AHM and fuzzy comprehensive evaluation to assess project risk and use this technique more widely.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	IEEE
ISBN:	978-1-5386-3135-5
ISSN:	2326-8239
Last Modified:	23 Oct 2022 13:59
URI:	https://orca.cardiff.ac.uk/id/eprint/112451

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