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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- What level of the important and type of the research changeable of the research ( the strategic planning for the taxes and investment) in the research organization ?
- Is there any relation of the join and effect of the changeable of the research (the strategic planning for the taxes and investment)in the research organization ?
Therefore this research depended a hypotheti
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conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation.
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This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.
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In this article, we aim to define a universal set consisting of the subscripts of the fuzzy differential equation (5) except the two elements and , subsets of that universal set are defined according to certain conditions. Then, we use the constructed universal set with its subsets for suggesting an analytical method which facilitates solving fuzzy initial value problems of any order by using the strongly generalized H-differentiability. Also, valid sets with graphs for solutions of fuzzy initial value problems of higher orders are found.
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Our goal in the present paper is to recall the concept of general fuzzy normed space and its basic properties in order to define the adjoint operator of a general fuzzy bounded operator from a general fuzzy normed space V into another general fuzzy normed space U. After that basic properties of the adjoint operator were proved then the definition of fuzzy reflexive general fuzzy normed space was introduced in order to prove that every finite dimensional general fuzzy normed space is fuzzy reflexive.
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