On the application of Valuation-Based Systems in the assessment of the probability bounds of Hazardous Material transportation accidents occurrence

An important issue in Hazardous Material (hazmat) transportation risk assessment is to evaluate the probability bounds of accidents occurrence, whose values are difficult to be estimated due to its low frequency and the related lack of statistical data. This paper presents an original approach to integrate uncertainty in the quantitative analysis of hazmat transportation accidents. The proposed approach is based on the use of Valuation-Based Systems (VBSs) and belief functions theory. Furthermore, we propose to identify the factors for which the reduction of epistemic uncertainty (imprecision) gives the greatest impact on the uncertainty of the final results by using some proposed measures. The applicability and generality of the proposed approach is demonstrated on a case study.

[1]  Thierry Denoeux,et al.  Risk assessment based on weak information using belief functions: a case study in water treatment , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[2]  William F. Caselton,et al.  Decision making with imprecise probabilities: Dempster‐Shafer Theory and application , 1992 .

[3]  Arthur P. Dempster,et al.  Upper and Lower Probabilities Induced by a Multivalued Mapping , 1967, Classic Works of the Dempster-Shafer Theory of Belief Functions.

[4]  Jia Jia,et al.  A Mission-oriented Risk Assessment Methodology for Naval Vessel Fire Caused by Non-contact Explosions Using Bayesian Networks☆ , 2013 .

[5]  B. M. Hill,et al.  Theory of Probability , 1990 .

[6]  Faisal Khan,et al.  Quantitative risk analysis of offshore drilling operations: A Bayesian approach , 2013 .

[7]  Audun Jøsang Cumulative and Averaging Fission of Beliefs , 2010, Inf. Fusion.

[8]  William Marsh,et al.  Using Bayesian Networks to Model Accident Causation in the UK Railway Industry , 2004 .

[9]  M Sam Mannan,et al.  Utilization of accident databases and fuzzy sets to estimate frequency of HazMat transport accidents. , 2009, Journal of hazardous materials.

[10]  Hong Xu Valuation-based systems for decision analysis using belief functions , 1997, Decis. Support Syst..

[11]  Mohamed Sallak,et al.  Reliability assessment for multi-state systems under uncertainties based on the Dempster–Shafer theory , 2013 .

[12]  Prakash P. Shenoy On Spohn's Theory of Epistemic Beliefs , 1990, IPMU.

[13]  Mohamed Sallak,et al.  Application of evidential networks in quantitative analysis of railway accidents , 2013 .

[14]  Philippe Smets The transferable belief model and other interpretations of Dempster-Shafer's model , 1990, UAI.

[15]  Vasiliki Kazantzi,et al.  Risk informed optimization of a hazardous material multi-periodic transportation model , 2011 .

[16]  Jay D. Johnson,et al.  A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory , 2007 .

[17]  M. Elisabeth Paté-Cornell,et al.  Uncertainties in risk analysis: Six levels of treatment , 1996 .

[18]  S. Kaplan,et al.  On The Quantitative Definition of Risk , 1981 .

[19]  Benoît Iung,et al.  Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas , 2012, Eng. Appl. Artif. Intell..

[20]  Bruce R. Ellingwood,et al.  Risk-averse decision-making for civil infrastructure exposed to low-probability, high-consequence events , 2012, Reliab. Eng. Syst. Saf..

[21]  Paolo Trucco,et al.  A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation , 2008, Reliab. Eng. Syst. Saf..

[22]  Philippe Smets,et al.  The Transferable Belief Model , 1994, Artif. Intell..

[23]  Luigi Portinale,et al.  Bayesian networks in reliability , 2007, Reliab. Eng. Syst. Saf..

[24]  Prakash P. Shenoy,et al.  Valuation-based systems: a framework for managing uncertainty in expert systems , 1992 .

[25]  Didier Dubois,et al.  Inference in Possibilistic Hypergraphs , 1990, IPMU.

[26]  P. Walley Statistical Reasoning with Imprecise Probabilities , 1990 .

[27]  Riccardo Minciardi,et al.  Risk Averse Routing of Hazardous Materials with Scheduled Delays , 2010 .

[28]  Prakash P. Shenoy,et al.  Conditional independence in valuation-based systems , 1994, Int. J. Approx. Reason..

[29]  Ingrid Bouwer Utne,et al.  Human Fatigue’s Effect on the Risk of Maritime Groundings - A Bayesian Network Modeling Approach , 2014 .

[30]  N Jayasuriya,et al.  A Bayesian network model to assess the public health risk associated with wet weather sewer overflows discharging into waterways. , 2012, Water research.

[31]  A. Farina,et al.  An Application of Evidential Networks to Threat Assessment , 2009, IEEE Transactions on Aerospace and Electronic Systems.

[32]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[33]  Prakash P. Shenoy,et al.  Valuation-based systems for propositional logic , 1991 .

[34]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[35]  Prakash P. Shenoy,et al.  Binary join trees for computing marginals in the Shenoy-Shafer architecture , 1997, Int. J. Approx. Reason..

[36]  Luigi Chisci,et al.  An approach to threat assessment based on evidential networks , 2007, 2007 10th International Conference on Information Fusion.

[37]  L. N. Kanal,et al.  Uncertainty in Artificial Intelligence 5 , 1990 .

[38]  Philippe Smets,et al.  Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem , 1993, Int. J. Approx. Reason..

[39]  Christophe Simon,et al.  Comparing Evidential Graphical Models for Imprecise Reliability , 2010, SUM.

[40]  Xulei Wang,et al.  Analysis of Factors that Influence Hazardous Material Transportation Accidents Based on Bayesian Networks: A Case Study in China , 2012 .

[41]  Prakash P. Shenoy,et al.  Axioms for probability and belief-function proagation , 1990, UAI.

[42]  Terje Aven,et al.  Interpretations of alternative uncertainty representations in a reliability and risk analysis context , 2011, Reliab. Eng. Syst. Saf..

[43]  Steffen L. Lauritzen,et al.  Local computation with valuations from a commutative semigroup , 1997, Annals of Mathematics and Artificial Intelligence.

[44]  Renee M. Clark,et al.  A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables. , 2009, Risk analysis : an official publication of the Society for Risk Analysis.

[45]  Ricardo Aguasca-Colomo,et al.  Dempster-Shafer Theory Based Ship-Ship Collision Probability Modelling , 2013, EUROCAST.

[46]  Prakash P. Shenoy,et al.  A valuation-based language for expert systems , 1989, Int. J. Approx. Reason..

[47]  Prakash P. Shenoy,et al.  Using Dempster-Shafer's belief-function theory in expert systems , 1992, Defense, Security, and Sensing.

[48]  D Warner North,et al.  Probability Theory and Consistent Reasoning , 2010, Risk analysis : an official publication of the Society for Risk Analysis.

[49]  A. Dawid Conditional Independence in Statistical Theory , 1979 .

[50]  Philippe Weber,et al.  Bayesian networks inference algorithm to implement Dempster Shafer theory in reliability analysis , 2008, Reliab. Eng. Syst. Saf..

[51]  Herbert H. Einstein,et al.  Risk analysis during tunnel construction using Bayesian Networks: Porto Metro case study , 2011 .

[52]  Yongtae Park,et al.  Assessing the risks of service failures based on ripple effects: A Bayesian network approach , 2013 .

[53]  Sou-Sen Leu,et al.  Bayesian-network-based safety risk assessment for steel construction projects. , 2013, Accident; analysis and prevention.

[54]  Mohamed Sallak,et al.  Extended Component Importance Measures Considering Aleatory and Epistemic Uncertainties , 2013, IEEE Transactions on Reliability.

[55]  Jin Wang,et al.  Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River , 2013, Reliab. Eng. Syst. Saf..

[56]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.