Handling Human-Centered Systems Uncertainty Using Fuzzy Logics - A Review
Isabel L. Nunes*
Identifiers and Pagination:Year: 2010
First Page: 38
Last Page: 48
Publisher Id: TOERGJ-3-38
Article History:Received Date: 16 /04 /2010
Revision Received Date: 13 /05 /2010
Acceptance Date: 30 /05 /2010
Electronic publication date: 9/8/2010
Collection year: 2009
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The analysis of human-centered systems (HCS) is complex, involving vagueness, uncertainty and ill-defined data. The subjective nature of human classifications renders classical logics approaches almost useless to deal with HCS. Fuzzy Logics (FL) provides a mathematical framework for the systematic treatment of vagueness and imprecision; facilitates the elicitation and encoding of uncertainty-related knowledge; and a flexible representation mechanism for dealing with vague data. The broad variety of fuzzy operators covers the continuum from union operators to intersection operators, including average operators. This paper presents several application examples of FL in HCS analysis, namely related with Ergonomics and Safety Analysis.