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An Algorithm for Producing Fuzzy Negations via Conical Sections

Department of Civil Engineering Section of Mathematics and Informatics, Democritus University of Thrace, 67100 Kimeria, Greece
Author to whom correspondence should be addressed.
Algorithms 2019, 12(5), 89;
Received: 31 March 2019 / Revised: 18 April 2019 / Accepted: 25 April 2019 / Published: 27 April 2019
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In this paper we introduced a new class of strong negations, which were generated via conical sections. This paper focuses on the fact that simple mathematical and computational processes generate new strong fuzzy negations, through purely geometrical concepts such as the ellipse and the hyperbola. Well-known negations like the classical negation, Sugeno negation, etc., were produced via the suggested conical sections. The strong negations were a structural element in the production of fuzzy implications. Thus, we have a machine for producing fuzzy implications, which can be useful in many areas, as in artificial intelligence, neural networks, etc. Strong Fuzzy Negations refers to the discrepancy between the degree of difficulty of the effort and the significance of its results. Innovative results may, therefore, derive for use in literature in the specific field of mathematics. These data are, moreover, generated in an effortless, concise, as well as self-evident manner. View Full-Text
Keywords: fuzzy implication; fuzzy negation; dual negation; conical sections fuzzy implication; fuzzy negation; dual negation; conical sections

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Souliotis, G.; Papadopoulos, B. An Algorithm for Producing Fuzzy Negations via Conical Sections. Algorithms 2019, 12, 89.

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