Further development of a causal model for air transport safety (CATS) : the complete model

This presentation looks at the further development of a causal model for air transport safety (CATS

Методи оцінки ризиків в інформаційній системі аналізу екологічного стану басейну малої ріки

В інформаційній системі аналізу стану басейну малої ріки запропоновано методи оцінки ризиків на основі імовірнісних та статистичних оцінок, формалізації моделі гри з природою, прогнозування процесів підтоплення земель з використанням ланцюгів Маркова, розглянуто багато критеріальні моделі ризиків.In informational and analytical system of the small rivers’ ecological condition estimation the methods of risks modelling on the basis of likelihood and statistical estimations, formalization of models of game with nature, risk modelling and forecasting processes flooded lands using Markov chains are offered, multicriteria models of risks are considered

TU Delft expert judgment data base

We review the applications of structured expert judgment uncertainty quantification using the “classical model” developed at the Delft University of Technology over the last 17 years [Cooke RM. Experts in uncertainty. Oxford: Oxford University Press; 1991; Expert judgment study on atmospheric dispersion and deposition. Report Faculty of Technical Mathematics and Informatics No.01-81, Delft University of Technology; 1991]. These involve 45 expert panels, performed under contract with problem owners who reviewed and approved the results. With a few exceptions, all these applications involved the use of seed variables; that is, variables from the experts’ area of expertise for which the true values are available post hoc. Seed variables are used to (1) measure expert performance, (2) enable performance-based weighted combination of experts’ distributions, and (3) evaluate and hopefully validate the resulting combination or “decision maker”. This article reviews the classical model for structured expert judgment and the performance measures, reviews applications, comparing performance-based decision makers with “equal weight” decision makers, and collects some lessons learned

Experience with expert judgement : the TU delft expert judgment data

This chapter explores the topic of experience with expert judgment and the TU delft expert judgment dat

Fifteen years of expert judgement at TUDelft

Over the last fifteen Delft University of Technology (both the Safety Science Group and the Department of Mathematics of TUDelft) has developed methods and tools to support the formal application of expert judgement. Over 800 experts assessed over 4000 variables, in total representing more than 80,000 elicited questions. Applications were made in a variety of sectors, such as nuclear applications, the chemical and gas industries, toxicity of chemicals, external effects (pollution, waste disposal sites, inundation, volcano eruptions), aerospace sector and aviation sector, the occupational sector, the health sector, and the banking sector. The techniques developed at TUDelft can be applied to give either quantitative assessments or just qualitative and comparative assessments. The application of these techniques is driven by a number of principles, including scrutability, fairness, neutrality, and performance control. The overall goal of these formal methods is to achieve rational consensus in the resulting assessments. Performance criteria are based on control assessments, that is, assessments of uncertain quantities, closely resembling the variables of interest, for which true values (e.g., from experiments) are known post hoc. The use of empirical control assessments is a distinctive feature of the Delft methods. A Procedure Guide for Structured Expert Judgement is published by the European Commission as EUR 18820. This paper highlights the comparative assessments for which the Safety Science Group was the prime responsible