FINs: lattice theoretic tools for improving prediction of sugar production from populations of measurements

Authors:
V. G. Kaburlasos
Affiliations:
Dept. of Ind. Informatics, Technol. Educ.al Instn. of Kavala, Greece
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2004

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Abstract

This paper presents novel mathematical tools developed during a study of an industrial-yield prediction problem. The set F of fuzzy interval numbers, or FINs for short, is studied in the framework of lattice theory. A FIN is defined as a mapping to a metric lattice of generalized intervals, moreover it is shown analytically that the set F of FINs is a metric lattice. A FIN can be interpreted as a convex fuzzy set, moreover a statistical interpretation is proposed here. Algorithm CALFIN is presented for constructing a FIN from a population of samples. An underlying positive valuation function implies both a metric distance and an inclusion measure function in the set F of FINs. Substantial advantages, both theoretical and practical, are shown. Several examples illustrate geometrically on the plane both the utility and the effectiveness of novel tools. It is outlined comparatively how some of the proposed tools have been employed for improving prediction of sugar production from populations of measurements for Hellenic Sugar Industry, Greece.