Membership functions II: Trends in fuzziness and implications

Juan Carlos Santamarina; Jean Lou Chameau

doi:10.1016/S0888-613X(87)80004-X

Membership functions II: Trends in fuzziness and implications

Juan Carlos Santamarina, Jean Lou Chameau^*

^*Corresponding author for this work

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

22 Scopus citations

Abstract

Results from a set of questionnaires designed to compare methods of obtaining membership functions were analyzed to identify general trends in fuzziness. It was found that fuzziness in comprehension is always reflected in the answer; concepts such as difficulty, imprecision, and shape of membership functions are clearly interrelated; and the transition between crisp extremes through fuzziness has characteristic manifestations. Emphasis is placed on the practical implications of these ideas; applications include developing standard and type II fuzzy sets, improving the completeness and consistency of available data, and supporting the development of knowledge-based systems using fuzzy sets.

Original language	English (US)
Pages (from-to)	303-317
Number of pages	15
Journal	International Journal of Approximate Reasoning
Volume	1
Issue number	3
DOIs	https://doi.org/10.1016/S0888-613X(87)80004-X
State	Published - Jul 1987
Externally published	Yes

Keywords

fuzziness
fuzzy sets
hedges
knowledge elicitation
membership functions
uncertainty

ASJC Scopus subject areas

Software
Artificial Intelligence
Theoretical Computer Science
Applied Mathematics

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10.1016/S0888-613X(87)80004-X

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title = "Membership functions II: Trends in fuzziness and implications",

abstract = "Results from a set of questionnaires designed to compare methods of obtaining membership functions were analyzed to identify general trends in fuzziness. It was found that fuzziness in comprehension is always reflected in the answer; concepts such as difficulty, imprecision, and shape of membership functions are clearly interrelated; and the transition between crisp extremes through fuzziness has characteristic manifestations. Emphasis is placed on the practical implications of these ideas; applications include developing standard and type II fuzzy sets, improving the completeness and consistency of available data, and supporting the development of knowledge-based systems using fuzzy sets.",

keywords = "fuzziness, fuzzy sets, hedges, knowledge elicitation, membership functions, uncertainty",

author = "Santamarina, {Juan Carlos} and Chameau, {Jean Lou}",

note = "Funding Information: The work described in this paper was performed at Purdue University. Financial support was supported by the National Science Foundation, under Grant CEE-8304720, and the Presidential Young Investigator's Award (Grant ECE-8451026) to J. L. Chameau. This support is gratefully acknowledged. The authors express their thanks to the professors and students who answered the questionnaires. Thanks are extended to the reviewers for their constructive criticisms, which helped improve this paper.",

year = "1987",

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doi = "10.1016/S0888-613X(87)80004-X",

language = "English (US)",

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AU - Chameau, Jean Lou

N1 - Funding Information: The work described in this paper was performed at Purdue University. Financial support was supported by the National Science Foundation, under Grant CEE-8304720, and the Presidential Young Investigator's Award (Grant ECE-8451026) to J. L. Chameau. This support is gratefully acknowledged. The authors express their thanks to the professors and students who answered the questionnaires. Thanks are extended to the reviewers for their constructive criticisms, which helped improve this paper.

PY - 1987/7

Y1 - 1987/7

N2 - Results from a set of questionnaires designed to compare methods of obtaining membership functions were analyzed to identify general trends in fuzziness. It was found that fuzziness in comprehension is always reflected in the answer; concepts such as difficulty, imprecision, and shape of membership functions are clearly interrelated; and the transition between crisp extremes through fuzziness has characteristic manifestations. Emphasis is placed on the practical implications of these ideas; applications include developing standard and type II fuzzy sets, improving the completeness and consistency of available data, and supporting the development of knowledge-based systems using fuzzy sets.

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KW - fuzzy sets

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ER -

Membership functions II: Trends in fuzziness and implications

Abstract

Keywords

ASJC Scopus subject areas

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