@inproceedings{aa42a49d5c31473aab09cb6368002bf6,
title = "A hybrid approach for fault tree analysis combining probabilistic method with fuzzy numbers",
abstract = "Fault tree analysis (FTA) is widely used for safety analysis of large and complex engineering systems such as nuclear power plants. Since FTA utilizes failure rate of every individual basic event constructing the tree, safety analysts have to provide probabilistic failure rate of every basic event in advance. However, it is often very difficult to exactly estimate the probability failure rates due to insufficient data, environment changing or new components. Fuzzy numbers can be applied to overcome the limitations of conventional FTA to predict the failure rate of basic events by handling linguistic terms. This study proposes a hybrid framework called Fuzzy Technique – based Fault Tree Analysis (FTFTA) to solve the problem and describes its procedures using a case study for emergency core cooling system of a typical nuclear reactor.",
keywords = "Fault tree analysis, Probabilistic failure rate, Fuzzy failure rate, Safety analysis.",
author = "Julwan Purba and Jie Lu and Da Ruan and Guangquan Zhang and Jan Wagemans",
note = "Score = 3; ICAISC 2010 - 10th International Conference on Artificial Intelligence and Soft Computing ; Conference date: 13-06-2010 Through 17-06-2010",
year = "2010",
month = jun,
language = "English",
isbn = "978-3-642-13207-0",
volume = "2",
series = "Lecture Notes in Artifical Intellignece (LNAI)",
number = "6113",
pages = "194--201",
booktitle = "Artificial Intelligence and Soft Computing",
}