Application of importance measures to transport industry: Computation using Bayesian networks and Fault Tree Analysis

Mahboob, Qamar; Schöne, Eric; Kunze, Michael; Trinckauf, Jochen; Maschek, Ulrich

doi:10.1109/icqr2mse.2012.6246180

Cited by 5 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For further readings on BNs and IDs and their application to different industries we refer to Ahmed (2010), Heredia-Zavoni et al (2012), Jensen and Nielsen (2007), Lentz (2007), Mahboob et al (2012b), Mohaghegh et al (2009), andStraub andKiureghian (2010).…”

Section: Influence Diagram (Id)mentioning

confidence: 99%

Investment into Human Risks in Railways and Decision Optimization

Mahboob¹,

Schöne

Maschek

et al. 2015

Human and Ecological Risk Assessment: An International Journal

View full text Add to dashboard Cite

The Life Quality Index (LQI) is a rational way to establish a relationship among the resources utilized to improve human safety and the expected fatalities that can be avoided by safety improvement. This article uses the LQI approach to quantify the social benefits of a number of safety management plans for a railway facility such as level crossing (LC). We apply influence diagrams (IDs), which are the extensions of Bayesian Networks, to model and assess the life safety risks. In IDs, problems of probabilistic inference, economics-based utility values, and decision alternatives are combined and optimized. The optimal decision, which maximizes total benefits to society, is obtained for the LC. As low as reasonably practicable (ALARP) case, and is a widely accepted risk acceptance criteria in the railway industry. According to the ALARP, there exists a so-called tolerable region between the regions of intolerable and negligible risks. In the tolerable region, risk is undertaken only if a benefit is desired. To quantify socioeconomic benefits, one needs to have an additional risk acceptance criterion such as LQI. In this article we apply and discuss the advantages of the LQI and the IDs for a number of safety management plans for railway LCs.

show abstract

Section: Influence Diagram (Id)mentioning

confidence: 99%

Investment into Human Risks in Railways and Decision Optimization

Mahboob¹,

Schöne

Maschek

et al. 2015

Human and Ecological Risk Assessment: An International Journal

View full text Add to dashboard Cite

show abstract

“…Also, it is found that sea-sonal changes have a considerable impact on prognostics involving railway turnouts. Mahboob et al (2012) summarised a number of Component Importance Measures (CIM), deriving the computation of the CIM using Bayesian Networks (BNs) and Fault Tree Analysis (FTA). It has recently been presented that the eff ect of weather on railway turnouts can be evaluated through a failure prediction model based on Bayesian Networks (Guang et al, 2017).…”

Section: Introductionmentioning

confidence: 99%