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A fuzzy-bayesian model for risk assessment in power plant projects

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posted on 2023-03-07, 23:47 authored by Muhammad Saiful Islam, Madhav Nepal
Cost overrun in power plant projects is a global problem. Assessing potential risks at preliminary stage of the project is important to control cost overrun. Existing models are discovered as ineffective for assessing cost overrun risks in power plant projects due to two basic limitations- i) incapable to handle subjective biases in riskassessment and ii) complex relationship among the risk factors. A novel method based on the combination of fuzzy logic and Bayesian belief network has been developed, which can solve both drawbacks of the existing models and provides the best result for finding inherent risks in power plant projects. This model assists the project managers providing early warning to manage the critical risks. It also helps to reach a realistic budget considering the costs of potential and critical risks in the estimation process, which consequently reduces the cost overrun of power plant projects.

History

Volume

100

Start Page

963

End Page

970

Number of Pages

8

eISSN

1877-0509

ISSN

1877-0509

Publisher

Elsevier

Additional Rights

CC BY-NC-ND 4.0

Language

en

Peer Reviewed

  • Yes

Open Access

  • Yes

Acceptance Date

2016-10-04

External Author Affiliations

Queensland University of Technology

Era Eligible

  • Yes

Journal

Procedia Computer Science

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