ساخت و مدیریت ارزش های زبانی
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ساخت و مدیریت ارزش های زبانی

عنوان فارسی مقاله: ساخت و مدیریت ارزش های زبانی چند دانه ای بر اساس اصطلاحات زبانی و مجموعه های فازی آنها
عنوان انگلیسی مقاله: Constructing and Managing Multi-Granular Linguistic Values Based on Linguistic Terms and Their Fuzzy Sets
مجله/کنفرانس: دسترسی – IEEE Access
رشته های تحصیلی مرتبط: مهندسی کامپیوتر
کلمات کلیدی فارسی: متغیر زبانی، حصار زبانی، اصطلاح زبانی دوتایی، ارزش های زبانی چند دانه ای، تصمیم گیری زبانی
کلمات کلیدی انگلیسی: Linguistic variable, linguistic hedge, 2-tuple linguistic term, multi-granular linguistic values, linguistic decision making
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1109/ACCESS.2019.2948847
دانشگاه: School of Science, Xihua University, Chengdu 610039, China
ناشر: آی تریپل ای - IEEE
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 4.641 در سال 2018
شاخص H_index: 56 در سال 2019
شاخص SJR: 0.609 در سال 2018
شناسه ISSN: 2169-3536
شاخص Quartile (چارک): Q2 در سال 2018
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 16
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13894
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


I. Introduction


II. Preliminaries


III. Formal Linguistic Concept of Linguistic Value


IV. The Formal 2-Tuple Linguistic Concept


V. The Hierarchy of Formal Linguistic Concepts


Authors


Figures


References

نمونه متن انگلیسی مقاله

Abstract


Constructing and managing multi-granular linguistic values are more and more important for linguistic decision making in big data or social computing environments, linguistic variable is the fundamental of constructing and managing multi-granular linguistic values. Based on analysis of linguistic values and drawbacks of symbolic or fuzzy set methods in processing linguistic information, a linguistic value is expressed by a formal linguistic concept, which is constructed by a linguistic term and it’s fuzzy sets, i.e., intension (name) and extension (meaning) of the concept are a linguistic term and it’s fuzzy sets. A new symbolic translation based on fuzzy sets is provided to obtain formal 2-tuple linguistic concepts, which are continuous formal linguistic concepts. By using linguistic hedges, the hierarchy of multi-granular formal linguistic concepts is constructed, and managing multi-granular linguistic values is carried out by a new transformation function between formal linguistic concepts of the hierarchy. Cases study shows that the proposed method combines advantages of symbolic approaches and fuzzy set methods in linguistic information processing and overcomes their drawbacks due to fuzzy sets and linguistic term as entity in linguistic information processing based on formal linguistic concepts, intensions are utilized to deal with linguistic information and extensions are used to represent meanings and obtain natural or artificial language concepts. It seems that constructing and managing multi-granular linguistic values via formal linguistic concepts is an useful and alternative method in linguistic information processing.


Introduction


The concept of linguistic variable plays a pivotal role in all applications of fuzzy logic, especially in computing with words or linguistic information processing [3]–[۶]. Formally, linguistic variable is defined as [7]: A linguistic variable is characterized by a quintuple (L, H, U, G, M), in which L is the name of the variable; H denotes the term set of L, i.e., the set of names of linguistic values of L, with each value being a fuzzy variable denoted generically by X and ranging across a universe of discourse U which is associated with the base variable u; G is a syntactic rule (which usually takes the form of a grammar) for generating the names of values of L; and M is a semantic rule for associating its meaning with each L, M(X), which is a fuzzy subset of U. For example, height is a linguistic variable defined on the universe (0, 2.5m] and high is a linguistic value of height, the trapezoidal fuzzy set µhigh(u) = (1.7, 1.9, 2.5, 2.5) on (0, 2.5m] can be a semantic value or meaning of high. In practical applications, high can be utilized to express qualitative knowledge ‘‘Europeans are high’’ and meaning of high can be represented by µhigh(u), due to calculable character of fuzzy sets, linguistic knowledge ‘‘Europeans are high’’ can be further processed by using µhigh(u) in a knowledge system.

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