Benchmark exercise on expert judgment techniques in PSA Level 2

Cojazzi, G.; Fogli, Daniela; Grassini, G; Gelder, Pieter De; Gryffroy, D.; Bolado, Ricardo; Hofer, Ėduard; Virolainen, Reino; Coe, Ian; Bassanelli, A.; Puga, Jorge López; Papazoglou, Ioannis A.; Zuchuat, Olivier; Cazzoli, E.G.; Eyink, Jürgen; Guida, Giovanni; Pinola, L.; Pulkkinen, Urho; Simola, Kaisa; Winterfeldt, Detlof von; Valeri, A.

doi:10.1016/s0029-5493(01)00404-6

Cited by 8 publications

(2 citation statements)

References 4 publications

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“…More recently developed methods have been applied to very complex problems such as nuclear reactor safety (28) or terrorism risk assessment. (29) The Joint Research Center of the European Commission conducted a comprehensive study of such procedures and identified three of them, the GRS method, the KEEJAM method, (30) and the NUREG-1150 method, (28,31,32) as the most reliable (33) (for an overview over these techniques, see Bouzaïène et al (24) ). While these methods are very well developed for complex problems, they do not address the problem of time pressure.…”

Section: Probability Elicitation Methodsmentioning

confidence: 99%

Probability Elicitation Under Severe Time Pressure: A Rank‐Based Method

Jaspersen¹,

Montibeller

2015

Risk Analysis

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Probability elicitation protocols are used to assess and incorporate subjective probabilities in risk and decision analysis. While most of these protocols use methods that have focused on the precision of the elicited probabilities, the speed of the elicitation process has often been neglected. However, speed is also important, particularly when experts need to examine a large number of events on a recurrent basis. Furthermore, most existing elicitation methods are numerical in nature, but there are various reasons why an expert would refuse to give such precise ratio-scale estimates, even if highly numerate. This may occur, for instance, when there is lack of sufficient hard evidence, when assessing very uncertain events (such as emergent threats), or when dealing with politicized topics (such as terrorism or disease outbreaks). In this article, we adopt an ordinal ranking approach from multicriteria decision analysis to provide a fast and nonnumerical probability elicitation process. Probabilities are subsequently approximated from the ranking by an algorithm based on the principle of maximum entropy, a rule compatible with the ordinal information provided by the expert. The method can elicit probabilities for a wide range of different event types, including new ways of eliciting probabilities for stochastically independent events and low-probability events. We use a Monte Carlo simulation to test the accuracy of the approximated probabilities and try the method in practice, applying it to a real-world risk analysis recently conducted for DEFRA (the U.K. Department for the Environment, Farming and Rural Affairs): the prioritization of animal health threats.

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Section: Probability Elicitation Methodsmentioning

confidence: 99%

Probability Elicitation Under Severe Time Pressure: A Rank‐Based Method

Jaspersen¹,

Montibeller

2015

Risk Analysis

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show abstract

“…The aim of the study was to understand the relative weightings that are assigned to a number of driver behaviors and thereby to construct a Safety Index. Finally, in (Pulkkinen & Holmberg, 1997;Simola & Virolainen, 2000;Cojazzi & Fogli, 2000), the Delphi method was proposed for several kinds of probabilistic safety assessments, including road safety.…”

Section: The Delphi Methods and Its Application In Road Safety Studiesmentioning

confidence: 99%

A Multiple Criteria Decision‐Making Approach for Prioritizing Accident Hotspots in the Absence of Crash Data

2010

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In an efficient transportation system, traffic safety is an important issue and it is influenced by many factors. In a country like Iran, until now safety improvements are mainly concentrated on road engineering activities, without much attention for vehicle technology or driving behavior. One important aspect of road safety engineering activities is the so-called treatment of hotspots or dangerous accident locations. Until recently, accident hotspots were identified and remedied by the experts' personal judgments and a hand-full of statistics without taking into account other important factors such as geometric and traffic conditions of the road network. This paper therefore aims to define and identify the criteria for accident hotspots, then giving a value to each criterion in order to develop a model to prioritize accident hotspots when traffic accident data is not available. To do this, the "Delphi" method has been adopted and a prioritization model is produced by the use of a "Multiple Criteria Decision Making" (MCDM) method. The procedure is illustrated on a collection of 20 road sections in Iran. In addition, the model is validated against an existing database of road sections containing safe locations and hotspots. Finally, a sensitivity analysis is carried out on the proposed method.

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Expert Judgment Quantification

Daim

2013

Research and Technology Management in the Electricity Industry

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Benchmark exercise on expert judgment techniques in PSA Level 2

Cited by 8 publications

References 4 publications

Probability Elicitation Under Severe Time Pressure: A Rank‐Based Method

Probability Elicitation Under Severe Time Pressure: A Rank‐Based Method

A Multiple Criteria Decision‐Making Approach for Prioritizing Accident Hotspots in the Absence of Crash Data

Expert Judgment Quantification

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