Handling Human-Centered Systems Uncertainty Using Fuzzy Logics – A Review

Isabel L. Nunes

doi:10.2174/1875934301003010038

Handling Human-Centered Systems Uncertainty Using Fuzzy Logics – A Review

Isabel L. Nunes

DEMI - Departamento de Engenharia Mecânica e Industrial

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	38-48
Journal	The Ergonomics Open Journal
Volume	3
Issue number	NA
DOIs	https://doi.org/10.2174/1875934301003010038
Publication status	Published - 1 Jan 2010

Access to Document

10.2174/1875934301003010038

Cite this

@article{4ec250edd4f54a9da0e3d56b51dfca9d,

title = "Handling Human-Centered Systems Uncertainty Using Fuzzy Logics – A Review",

abstract = "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.",

keywords = "fuzzy logics, Human-centered Systems, ergonomics, safety",

author = "Nunes, {Isabel L.}",

year = "2010",

month = jan,

day = "1",

doi = "10.2174/1875934301003010038",

language = "English",

volume = "3",

pages = "38--48",

journal = "The Ergonomics Open Journal",

issn = "1875-9343",

publisher = "Bentham Science Publishers",

number = "NA",

}

TY - JOUR

T1 - Handling Human-Centered Systems Uncertainty Using Fuzzy Logics – A Review

AU - Nunes, Isabel L.

PY - 2010/1/1

Y1 - 2010/1/1

N2 - 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.

AB - 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.

KW - fuzzy logics

KW - Human-centered Systems

KW - ergonomics

KW - safety

U2 - 10.2174/1875934301003010038

DO - 10.2174/1875934301003010038

M3 - Article

SN - 1875-9343

VL - 3

SP - 38

EP - 48

JO - The Ergonomics Open Journal

JF - The Ergonomics Open Journal

IS - NA

ER -

Handling Human-Centered Systems Uncertainty Using Fuzzy Logics – A Review

Abstract

Access to Document

Fingerprint

Cite this