Type-one fuzzy logic for quantitatively defining imprecise linguistic terms in politics and public policy

Ashu M.G. Solo, Madan M. Gupta, Noriyasu Homma, Zeng Guang Hou

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

During a presidential forum in the 2008 U.S. presidential campaign, the moderator, Pastor Rick Warren, wanted Senator John McCain and then-Senator Barack Obama to define “rich” with a specific number. Warren wanted to know at what specific income level a person goes from being not rich to rich. The problem with this question is that there is no specific income at which a person makes the leap from being not rich to being rich. This is because “rich” is a fuzzy set, not a crisp set, with different incomes having different degrees of membership in the “rich” fuzzy set. Similarly, “middle class” and “poor” are fuzzy sets. Fuzzy logic is needed to properly ask and answer Warren’s question about quantitatively defining “rich.” Similarly, fuzzy logic is needed to properly ask and answer queries about quantitatively defining imprecise linguistic terms in politics and public policy like “middle class,” “poor,” “low inflation,” “medium inflation,” and “high inflation.” Imprecise terms like these in natural languages should be considered to have “qualitative definitions,” “quantitative definitions,” “crisp quantitative definitions,” and “fuzzy quantitative definitions.” This chapter provides much more information on the preceding.

Original languageEnglish
Title of host publicationResearch Methods
Subtitle of host publicationConcepts, Methodologies, Tools, and Applications
PublisherIGI Global
Pages67-83
Number of pages17
ISBN (Electronic)9781466674585
ISBN (Print)9781466674578
DOIs
Publication statusPublished - 2015 Jan 1

ASJC Scopus subject areas

  • Social Sciences(all)
  • Engineering(all)

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