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Fuzzy Interval Manipulation in Imprecise Decision Tables

D.J. Poling

Department of Computer Science

Clemson University

Clemson, SC 29634-1906 USA

[email protected]

Lois W. Hawkes

Department of Computer Science

Florida State University

Tallahassee, FL 32304 USA

[email protected]

February 12, 1993


Decision tables are a graphical method for representation of logical interrelationships (cause and effects) and offer a unique and extremely powerful alternative to standard flow charts and pseudocode which are usually used as logic representation schemata for computer science applications. Through certain techniques for extending the properties of decision tables, here-to-fore unrealized and unrecognized relationships among the various elements portrayed in the decision table become surprisingly apparent. Oft times these newly discovered relationships allow for a much more efficient and accurate codifying process, and many times point to additional program logic or alternatives to that program logic. Development of the extension of this powerful technique into the realm of fuzzy logic, has provided a tool for the application designer.

Fuzzy logic is a formal method developed for dealing with and manipulating, terms and values not of a crisp nature. Based upon fuzzy set theory, this method deals with the objects of a fuzzy set and their respective grades of membership in the set. With this tool, the designer is far better able to perceive and employ relationships which can not be dealt with satisfactorily using standard crisp methods and still succinctly communicate these concepts with other scientists.

This article explores the further extension of these methods to the preservation and manipulation of fuzzy intervals and demonstrates the use of these new principles and techniques by employing naive semantic interpretations.

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