The purpose of this paper is to shed light on the concept of fuzzy logic ,its application in linguistics ,especially in language teaching and the fuzziness of some lexical items in English.
Fuzziness means that the semantic boundaries of some lexical items are indefinite and ideterminate.Fuzzy logic provides a very precise approach for dealing with this indeterminacy and uncertainty which grows (among other reasons) out of human behavior and the effect of society.
The concept of fuzzy logic has emerged in the development of the theory of fuzzy set by Lotfi Zadeh(a professor of computer science at the university of California) in 1965.It can be thought of as the application side of the fuzzy set theory. In linguistics, few scholars have dealt with this phenomenon, among them, Lakoff (1972), Labov (1973), and Aitchison (1994). Consequently, very little literature is available on this concept in linguistics. The researcher has to collect bits of information scattered in various fields of knowledge.
The paper is of three sections: section one surveys briefly some of the semantic terms which are closely related to lexical fuzziness, since it is a problem of meaning by nature, like denotation versus connotation and intension versus extension. Section two is of two main parts. The first explores in detail the emergence of fuzzy logic, shedding light on its development and the criticism to it. The second part is devoted to lexical fuzziness, trying to discover its characteristics, the reasons behind its existence in languages, its relation to other similar concepts like vagueness, its application in teaching a second language and some other related titles.
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi
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