@inproceedings{453ed169ec9f4a458dad39ee8d416c8a,
title = "Approaches to bayesian network structure elicitation",
abstract = "Bayesian networks (BN) are increasingly popular as a modeling tool for engineering risk and reliability analysis. BNs consist of two parts: the qualitative dependence structure represented by a directed acyclic graph (DAG), and the quantification of local dependences through conditional probability distributions (CPDs). The derivation of the general dependence structure requires a profound understanding of the problem as well as an understanding of the modeling tool. Once the general structure is developed, the probability expert knows what CPDs need to be elicited through data, expert estimates or a combination of both.",
author = "K. Zwirglmaier and D. Straub",
note = "Publisher Copyright: {\textcopyright} 2017 Taylor & Francis Group, London.; 26th European Safety and Reliability Conference, ESREL 2016 ; Conference date: 25-09-2016 Through 29-09-2016",
year = "2017",
language = "English",
isbn = "9781138029972",
series = "Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016",
publisher = "CRC Press/Balkema",
pages = "56",
editor = "Lesley Walls and Matthew Revie and Tim Bedford",
booktitle = "Risk, Reliability and Safety",
}