On the fuzzy Bayesian inference of population annoyance level caused by noise exposure

León-Rojas, Juan-Miguel; Masero, Valentín; Morales, Montaña

doi:10.1145/952532.952580

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…In order to solve the above problems, León-Rojas et al (2003) proposed a fuzzy Bayesian partnership algorithm to estimate fuzzy likelihood and fuzzy prior probability. Using maximum likelihood solution, they avoided complicated likelihood function estimation and thus provided a way to simplify computation.…”

Section: Offshore Risk Consideration and Safety Assessment Methodsmentioning

confidence: 99%

An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

Ren

Jenkinson

Wang

et al. 2009

Journal of Offshore Mechanics and Arctic Engineering

142

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The operation of an offshore installation is associated with a high level of uncertainty because it usually operates in a dynamic environment in which technical and human and organizational malfunctions may cause possible accidents. This paper proposes a fuzzy Bayesian network (FBN) approach to model causal relationships among risk factors, which may cause possible accidents in offshore operations. The FBN model explicitly represents cause-and-effect assumptions between offshore engineering system variables that may be obscured under other modeling approaches like fuzzy reasoning and Monte Carlo risk analysis. The flexibility of the method allows for multiple forms of information to be used to quantify model relationships, including formally assessed expert opinions when quantitative data are lacking in early design stages with a high level of innovation or when only qualitative or vague statements can be made. The model is also a modular representation of uncertain knowledge due to randomness and vagueness. This makes the risk and safety analysis of offshore engineering systems more functional and easier in many assessment contexts. A case study of the collision risk between a floating production, storage and offloading unit and the authorized vessels due to human errors during operation is used to illustrate the application of the proposed model.

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Section: Offshore Risk Consideration and Safety Assessment Methodsmentioning

confidence: 99%

An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

Ren

Jenkinson

Wang

et al. 2009

Journal of Offshore Mechanics and Arctic Engineering

142

View full text Add to dashboard Cite

show abstract

“…Alternatives to BBN that seem less vulnerable to lack of knowledge are fuzzy Bayesian inference systems (FBI; Viertl, 1987), where conditional probabilities do not need to be perfectly known and input data can be of semi-quantitative nature. Léon-Rojas et al (2003) give an example of application of FBI to assess the annoyance level caused by noise exposure, where noise measurements are non-exact.…”

Section: Full Clorpt Modelling Of Pedogenesismentioning

confidence: 99%