A representation of human reliability using fuzzy concepts
Information Sciences: an International Journal - Application of Fuzzy Set Theory
An approach to human reliability on man-machine systems using error possibility
Fuzzy Sets and Systems
Fuzzy human reliability analysis on the Chernobyl accident
Fuzzy Sets and Systems
Fuzzy reliability assessment considering the influence of many factors on reliability
International Journal of Approximate Reasoning
An application of fuzzy concepts to modelling of reliability analysis
Fuzzy Sets and Systems
Gradual inference rules in approximate reasoning
Information Sciences: an International Journal
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Uncertainty in fault tree analysis: a fuzzy approach
Fuzzy Sets and Systems - Special issue on fuzzy methodology in system failure engineering
Subjective analysis of system reliability and its analyzer
Fuzzy Sets and Systems - Special issue on fuzzy methodology in system failure engineering
What are fuzzy rules and how to use them
Fuzzy Sets and Systems - Special issue dedicated to the memory of Professor Arnold Kaufmann
Fuzzy Modeling for Control
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems
Expert Systems with Applications: An International Journal
Human cognition as an intelligent decision support system for plastic products' design
Expert Systems with Applications: An International Journal
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The assessment of dependence among human errors is an important aspect of human reliability analysis. When dependence between two tasks exists, the probability of the operators' failure on one task is higher if they have failed on the preceding task, compared to when they have succeeded. In current practice, the task of assessing dependence among successive operator actions relies to a great extent to expert judgment, often with lack of traceability and repeatability. To overcome these limitations, this work presents a systematic framework for the elicitation of expert knowledge on the factors influencing the dependence between two successive tasks. The framework is based on a fuzzy expert system in which a set of transparent fuzzy logic rules is used to represent the relationship between the input factors and the conditional human error probability. The proposed modeling approach is applied to two tasks required in response to an accident scenario at a nuclear power plant. Given the methodological scope of the work, the fuzzy expert system is tested directly on a working model of dependence, whereas no actual exercise of expert judgment elicitation is carried out.