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Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "2-TUPLE LINGUISTIC"

1

Singh, Anjali, and Anjana Gupta. "Some Observations on 2-tuple Linguistic and Interval 2-tuple Linguistic Operators." International Journal of Mathematical, Engineering and Management Sciences 4, no. 2 (April 1, 2019): 327–36. http://dx.doi.org/10.33889/ijmems.2019.4.2-026.

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Анотація:
Literature of aggregation operators defined in the domains of linguistic and interval-valued linguistic information is extensive and vast. But, some operators are not well-defined and do not benefit the researchers. In this paper, we have highlighted the flaws in defining the operators and demonstrated them via examples. Further, some remedial suggestions for the improvement of the definitions are given.
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2

Wei, Guiwu. "Model for Multiple Attribute Decision Making Based on Picture 2-Tuple Linguistic Power Aggregation Operators." International Journal of Decision Support System Technology 11, no. 1 (January 2019): 35–65. http://dx.doi.org/10.4018/ijdsst.2019010103.

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Анотація:
In this article, the authors investigate the multiple attribute decision making problems with picture 2-tuple linguistic information. The utilized power average and power geometric operations used to develop some picture 2-tuple linguistic power aggregation operators: picture 2-tuple linguistic power weighted average (P2TLPWA) operator, picture 2-tuple linguistic power weighted geometric (P2TLPWG) operator, picture 2-tuple linguistic power ordered weighted average (P2TLPOWA) operator, picture 2-tuple linguistic power ordered weighted geometric (P2TLPOWG) operator, picture 2-tuple linguistic power hybrid average (P2TLPHA) operator and picture 2-tuple linguistic power hybrid geometric (P2TLPHG) operator. The prominent characteristic of these proposed operators is studied. This article has utilized these operators to develop some approaches to solve the picture 2-tuple linguistic multiple attribute decision making problems. Finally, a practical example for enterprise resource planning (ERP) system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.
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3

Abdullah, Saleem, Omar Barukab, Muhammad Qiyas, Muhammad Arif, and Sher Afzal Khan. "Analysis of Decision Support System Based on 2-Tuple Spherical Fuzzy Linguistic Aggregation Information." Applied Sciences 10, no. 1 (December 30, 2019): 276. http://dx.doi.org/10.3390/app10010276.

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Анотація:
The aim of this paper is to propose the 2-tuple spherical fuzzy linguistic aggregation operators and a decision-making approach to deal with uncertainties in the form of 2-tuple spherical fuzzy linguistic sets. 2-tuple spherical fuzzy linguistic operators have more flexibility than general fuzzy set. We proposed a numbers of aggregation operators, namely 2-tuple spherical fuzzy linguistic weighted average, 2-tuple spherical fuzzy linguistic ordered weighted average, 2-tuple spherical fuzzy linguistic hybrid average, 2-tuple spherical fuzzy linguistic weighted geometric, 2-tuple spherical fuzzy linguistic ordered geometric, and 2-tuple spherical fuzzy linguistic hybrid geometric operators. The distinguishing feature of these proposed operators is studied. At that point, we have used these operators to design a model to deal with multiple attribute decision-making issues under the 2-tuple spherical fuzzy linguistic information. Then, a practical application for best company selection for feeds is given to prove the introduced technique and to show its practicability and effectiveness. Besides this, a systematic comparison analysis with other existent methods is conducted to reveal the advantage of our method. Results indicate that the proposed method is suitable and effective for decision making problems.
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4

Liu, Xi, Zhifu Tao, Huayou Chen, and Ligang Zhou. "A MAGDM Method Based on 2-Tuple Linguistic Heronian Mean and New Operational Laws." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, no. 04 (August 2016): 593–627. http://dx.doi.org/10.1142/s0218488516500288.

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Анотація:
In this paper, we investigate the multiple attributes group decision making (MAGDM) problem with 2-tuple linguistic information. According to some closed operational laws of 2-tuple linguistic, some Algebra t-norm and s-norm based Heronian aggregation operators of 2-tuple linguistic information are put forward, the desired properties and the special cases where the parameters take different values are also discussed. Furthermore, a method of MAGDM under 2-tuple linguistic environment is proposed based on the Algebra t-norm and s-norm based 2-tuple linguistic Heronian mean operator or the Algebra t-norm and s-norm based 2-tuple linguistic weighted Heronian mean operator. Finally, a numerical example is presented to demonstrate the proposed method.
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5

Shan, Meng-Meng, Jian-Xin You, and Hu-Chen Liu. "Some Interval 2-Tuple Linguistic Harmonic Mean Operators and Their Application in Material Selection." Advances in Materials Science and Engineering 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/7034938.

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Анотація:
We investigate the multiple attribute group material selection problems in which the attribute values take the form of interval 2-tuple linguistic information. Firstly, some operational laws and possibility degree of interval 2-tuple linguistic variables are introduced. Then, we develop some interval 2-tuple linguistic aggregation operators called interval 2-tuple hybrid harmonic mean (ITHHM) operator, induced interval 2-tuple ordered weighted harmonic mean (I-ITOWHM) operator, and induced interval 2-tuple hybrid harmonic mean (I-ITHHM) operator and study some desirable properties of the I-ITOWHM operator. In particular, all these operators can be reduced to aggregate 2-tuple linguistic variables. Based on the I-ITHHM and the ITWHM (interval 2-tuple weighted harmonic mean) operators, an approach to multiple attribute group decision-making with interval 2-tuple linguistic information is proposed. Finally, a practical application to material selection problem is given to verify the developed approach and to demonstrate its practicality and effectiveness.
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6

Zuo, Yuting, and Chunfang Chen. "A New Fuzzy Multiple Attribute Decision Making Method Based on the Utility Transformation Functions." Symmetry 11, no. 3 (March 21, 2019): 418. http://dx.doi.org/10.3390/sym11030418.

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Анотація:
The 2-tuple linguistic information model (2TLIM) is a useful tool to avoid the loss of information, which has been widely adapted in the study of the multiple attribute decision making (MADM) problem. However, there is a limitation, the limitation is that the difference between the neighboring 2-tuple linguistic information is fixed regardless of the decision-makers’ attitude. In this paper, we define the utility transformation functions based on the 2-tuple linguistic utility to overcome the drawback. Firstly, by introducing the economic utility theory, the 2-tuple linguistic utility is defined, the 2-tuple linguistic utility parameter (2TLUP) and the 2-tuple linguistic marginal utility (2TLMU) are constructed to achieve the measurement of the decision-makers’ attitude. The utility transformation functions are developed on the decision-makers’ attitude. Secondly, the 2-tuple linguistic operational laws are presented with the extended Hamacher T-norm (TN) and T-conorm (TC). Subsequently, we propose the 2-tuple linguistic utility weighted average (2TLUWA) operator and the method of MADM. Lastly, the application and the comparison with the existing methods are summarized to verify the practicality and advantages of the proposed method of MADM.
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7

Wang, Jie, Jianping Lu, Guiwu Wei, Rui Lin, and Cun Wei. "Models for MADM with Single-Valued Neutrosophic 2-Tuple Linguistic Muirhead Mean Operators." Mathematics 7, no. 5 (May 17, 2019): 442. http://dx.doi.org/10.3390/math7050442.

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Анотація:
In this article, we expand the Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator with single-valued neutrosophic 2-tuple linguistic numbers (SVN2TLNs) to propose the single-valued neutrosophic 2-tuple linguistic Muirhead mean (SVN2TLMM) operator, the single-valued neutrosophic 2-tuple linguistic weighted Muirhead mean (SVN2TLWMM) operator, the single-valued neutrosophic 2-tuple linguistic dual Muirhead mean (SVN2TLDMM) operator, and the single-valued neutrosophic 2-tuple linguistic weighted dual Muirhead mean (SVN2TLWDMM) operator. Multiple attribute decision making (MADM) methods are then proposed using these operators. Finally, we utilize an applicable example for green supplier selection in green supply chain management to prove the proposed methods.
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8

Wang, Jie, Guiwu Wei, and Hui Gao. "Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information." Mathematics 6, no. 10 (October 13, 2018): 201. http://dx.doi.org/10.3390/math6100201.

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Анотація:
The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation operator used in modern information fusion theory, which is suitable to aggregate numerical values. The prominent characteristic of the MSM operator is that it can capture the interrelationship among multi-input arguments. Motivated by the ideal characteristic of the MSM operator, in this paper, we expand the MSM operator, generalized MSM (GMSM), and dual MSM (DMSM) operator with interval-valued 2-tuple linguistic Pythagorean fuzzy numbers (IV2TLPFNs) to propose the interval-valued 2-tuple linguistic Pythagorean fuzzy MSM (IV2TLPFMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy weighted MSM (IV2TLPFWMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy GMSM (IN2TLPFGMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy weighted GMSM (IV2TLPFWGMSM) operator, interval-valued 2-tuple linguistic Pythagorean fuzzy DMSM (IN2TLPFDMSM) operator, Interval-valued 2-tuple linguistic Pythagorean fuzzy weighted DMSM (IV2TLPFWDMSM) operator. Then the multiple attribute decision making (MADM) methods are developed with these three operators. Finally, an example of green supplier selection is used to show the proposed methods.
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9

Deng, Xiumei, Jie Wang, Guiwu Wei, and Mao Lu. "Models for Multiple Attribute Decision Making with Some 2-Tuple Linguistic Pythagorean Fuzzy Hamy Mean Operators." Mathematics 6, no. 11 (October 31, 2018): 236. http://dx.doi.org/10.3390/math6110236.

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Анотація:
The Hamy mean (HM) operator, as a useful aggregation tool, can capture the correlation between multiple integration parameters, and the 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs) are a special kind of Pythagorean fuzzy numbers (PFNs), which can easily describe the fuzziness in actual decision making by 2-tuple linguistic terms (2TLTs). In this paper, to consider both Hamy mean (HM) operator and 2TLPFNs, we combine the HM operator, weighted HM (WHM) operator, dual HM (DHM) operator, and dual WHM (DWHM) operator with 2TLPFNs to propose the 2-tuple linguistic Pythagorean fuzzy HM (2TLPFHM) operator, 2-tuple linguistic Pythagorean fuzzy WHM (2TLPFWHM) operator, 2-tuple linguistic Pythagorean fuzzy DHM (2TLPFDHM) operator and 2-tuple linguistic Pythagorean fuzzy DWHM (2TLPFDWHM) operator. Then some multiple attribute decision making (MADM) procedures are developed based on these operators. At last, an applicable example for green supplier selection is given.
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10

Naz, Sumera, Muhammad Akram, Mohammed M. Ali Al-Shamiri, Mohammed M. Khalaf, and Gohar Yousaf. "A new MAGDM method with 2-tuple linguistic bipolar fuzzy Heronian mean operators." Mathematical Biosciences and Engineering 19, no. 4 (2022): 3843–78. http://dx.doi.org/10.3934/mbe.2022177.

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Анотація:
<abstract><p>In this article, we introduce the 2-tuple linguistic bipolar fuzzy set (2TLBFS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into bipolar fuzzy set. The 2TLBFS is a better way to deal with uncertain and imprecise information in the decision-making environment. We elaborate the operational rules, based on which, the 2-tuple linguistic bipolar fuzzy weighted averaging (2TLBFWA) operator and the 2-tuple linguistic bipolar fuzzy weighted geometric (2TLBFWG) operator are presented to fuse the 2TLBF numbers (2TLBFNs). The Heronian mean (HM) operator, which can reflect the internal correlation between attributes and their influence on decision results, is integrated into the 2TLBF environment to analyze the effect of the correlation between decision factors on decision results. Initially, the generalized 2-tuple linguistic bipolar fuzzy Heronian mean (G2TLBFHM) operator and generalized 2-tuple linguistic bipolar fuzzy weighted Heronian mean (G2TLBFWHM) operator are proposed and properties are explained. Further, 2-tuple linguistic bipolar fuzzy geometric Heronian mean (2TLBFGHM) operator and 2-tuple linguistic bipolar weighted geometric Heronian mean (2TLBFWGHM) operator are proposed along with some of their desirable properties. Then, an approach to multi-attribute group decision-making (MAGDM) based on the proposed aggregation operators under the 2TLBF framework is developed. At last, a numerical illustration is provided for the selection of the best photovoltaic cell to demonstrate the use of the generated technique and exhibit its adequacy.</p></abstract>
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Більше джерел

Дисертації з теми "2-TUPLE LINGUISTIC"

1

Zettervall, Hang. "Fuzzy Set Theory Applied to Make Medical Prognoses for Cancer Patients." Doctoral thesis, Blekinge Tekniska Högskola [bth.se], Faculty of Engineering - Department of Mathematics and Natural Sciences, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00574.

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Анотація:
As we all know the classical set theory has a deep-rooted influence in the traditional mathematics. According to the two-valued logic, an element can belong to a set or cannot. In the former case, the element’s membership degree will be assigned to one, whereas in the latter case it takes the zero value. With other words, a feeling of imprecision or fuzziness in the two-valued logic does not exist. With the rapid development of science and technology, more and more scientists have gradually come to realize the vital importance of the multi-valued logic. Thus, in 1965, Professor Lotfi A. Zadeh from Berkeley University put forward the concept of a fuzzy set. In less than 60 years, people became more and more familiar with fuzzy set theory. The theory of fuzzy sets has been turned to be a favor applied to many fields. The study aims to apply some classical and extensional methods of fuzzy set theory in life expectancy and treatment prognoses for cancer patients. The research is based on real-life problems encountered in clinical works by physicians. From the introductory items of the fuzzy set theory to the medical applications, a collection of detailed analysis of fuzzy set theory and its extensions are presented in the thesis. Concretely speaking, the Mamdani fuzzy control systems and the Sugeno controller have been applied to predict the survival length of gastric cancer patients. In order to keep the gastric cancer patients, already examined, away from the unnecessary suffering from surgical operation, the fuzzy c-means clustering analysis has been adopted to investigate the possibilities for operation contra to nonoperation. Furthermore, the approach of point set approximation has been adopted to estimate the operation possibilities against to nonoperation for an arbitrary gastric cancer patient. In addition, in the domain of multi-expert decision-making, the probabilistic model, the model of 2-tuple linguistic representations and the hesitant fuzzy linguistic term sets (HFLTS) have been utilized to select the most consensual treatment scheme(s) for two separate prostate cancer patients. The obtained results have supplied the physicians with reliable and helpful information. Therefore, the research work can be seen as the mathematical complements to the physicians’ queries.
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2

Yi-RuWu and 吳宜茹. "Applying 2-Tuple Fuzzy Linguistic Representation in TOPSIS Group Decision-Making Model." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/95575976448428092716.

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Анотація:
碩士
國立成功大學
工業與資訊管理學系碩博士班
98
The approach of “technique for order preference by similarity to ideal solution (TOPSIS)” is usually considered as a multi-attribute decision-making (MADM) method. It can determine the ranking for all the alternatives based on the measurement of the distance between crisp data and ideal solution. In decision-making processes, decision-makers choose the appropriate domain to assess alternatives due to the nature of the attributes. This non-homogeneous information can be represented as values belonging to domains with different nature as numerical, interval valued or linguistic. In order to deal with ambiguity existing in decision-making information, the defuzzification method is adopted in the operations of fuzzy numbers; however, the loss of decision-making information may happen. The loss of information implies a lack of precision in the decision results. This motivates the proposed method to apply the 2-tuple fuzzy linguistic representation to replace the traditional linguistic variables. Moreover, the attributes’ weights are also key factors which affect decision results. The direct determination of each attribute’s weight by decision makers could be too subjective for a decision-making problem. In addition, when many aspects affect complex decision problems, relying on only one decision maker’s knowledge and experience could produce an unreliable consequence. To address these problems, we construct a TOPSIS group decision-making model which includes three stages. In the first stage, we transform the non-homogeneous information into the 2-tuple fuzzy linguistic representation. The second stage applies a two-step mathematical programming method which takes both decision maker's subjective opinion and objective information into account to determine attributes’ weights. Then we can rank all alternatives by the modified TOPSIS group decision-making model. Finally, a numerical example is performed using the proposed model to demonstrate its superiority, compared to Halouani et al. (2009). Key words: 2-tuple fuzzy linguistic representation; TOPSIS; MADM; group decision-making
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3

MALHOTRA, TANYA. "COMPUTATION WITH 2-TUPLE LINGUISTIC VARIABLES AND ITS APPLICATION IN MATRIX GAMES." Thesis, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19610.

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Анотація:
Making a decision entails selecting from a set of options based on a preliminary analy sis, which frequently includes human intervention and uncertainty. Besides, grasping the meaning communicated by information in a qualitative setting is necessary before making a further analysis. One of the most challenging issues is to deal with statements, human thoughts preferences, feelings, and so on because of the inherent character of natural lan guage. Over the years, much work has been taken to account for the ambiguity and impre cision of linguistic information by using the theory of fuzzy set and fuzzy linguistic-based approach. Several computational methods have been created to deal with uncertainty, par ticularly when it is not of a probabilistic character. Specifically, in 2000, a new model known as the “2-tuple linguistic representation model” arose, which improved numerous linguistic processes for handling complex decision-making issues. It facilitates a contin uous representation of the linguistic terms, and henceforth, research concerned with the 2-tuple model is profuse and worthwhile considering in deep. The introspection of the distinguished literature in the 2-tuple model enabled us to re alize that some limitations still persist in the existing uncertain 2-tuple models. This mo tivated us to improve the existing uncertain models to make their implementation more flexible and consistent in decision-making processes. Therefore, in our study, we have ad dressed the constraints and challenges associated with the existing 2-tuple model and have worked towards its development to enhance its applicability. Further, we have supported our study by applying the 2-tuple model in the domain of matrix games and decision anal ysis. This has enabled us to contribute to the researchers worldwide who are working in this field and are also looking for exploration. The thesis entitled “Computation with 2-tuple linguistic variable and its application in matrix games” comprises of six chapters followed by the summary and future scope. The bibliography and the list of publications are provided at the end of the thesis. The introductory Chapter 1 presents a short overview of computing with words 2- xiii tuple based linguistic model as well as its elementary application anticipated in distinct decision-making models followed by its extension. Thus, the current chapter creates a background and motivates this thesis’s work. The chapter is based on a review paper, “A systematic review of developments in the 2-tuple linguistic model and its applications in decision analysis,” published in Soft Computing, Springer (2020). The Chapter 2 entitled, “Group operations and properties for 2-tuple linguistic vari ables with its application” establish the basis for a theory of 2-tuple linguistic groups un der the given binary operation in a classical impression. In literature, the concept of fuzzy algebra has been a subject of research for many years and has made significant progress. Nevertheless, the abstract theory of linguistic groups is pristine and yet to be explored. The use of fuzzy linguistic concepts to represent practical situations with qualitative data has shown to be a powerful approach. Several computational techniques have been intro duced to alleviate the computation between linguistic terms. Among these computational techniques, the proposal of a 2-tuple linguistic model is a useful tool by easing out the computations and avoiding information loss when applied in some practical decision making situations. In the study of linguistic information, the aggregation of 2-tuple lin guistic labels is a crucial problem. Several computing models existing in the literature are well-suited to deal with this problem. However, it is noted that the existing opera tional laws are not satisfying the closure property. Moreover, to the best of knowledge, no theory has been developed to support the concept of linguistic groups. For this reason, the foundation of the theory of 2-tuple linguistic groups under a crisp binary operation is a milestone in this direction, overcoming the constraints of the existing operational laws which operate without information loss. The chapter has given a formal methodology to claim that the 2-tuple linguistic term set forms an algebraic structure group. Further, a similarity relation between the linguistic groups is obtained, and some properties of the operational laws, group isomorphic and homomorphic relation, have been discussed in detail. Lastly, the physical meaning of the abstract concept so developed has been showcased in bipolar graphs and matrix games. The chapter is based on a research paper entitled, “Group operations and isomorphic relation with the 2-tuple linguistic variables”, published in Soft Computing, springer 24, 18287–18300 (2020) and “Group isomorphic properties with some novel operational laws for 2-tuple linguistic variables and its appli cation in linguistic matrix games” Communicated in IEEE Transactions on Systems, Man, and Cybernetics: Systems. A qualitative decision making problems with linguistic term set where all plausible lin xiv guistic descriptors provided by experts have symmetric and uniform distribution has been investigated by several scholars. Obviously, it might not be suitable in practical life de cision problems since the experts may prefer linguistic labels distributed non-uniformly and non-symmetrically. Numerous studies have been developed on theoretical and prac tical applications to handle an unbalanced linguistic context. However, the current unbal anced linguistic computational models are complex and computationally more expensive. Therefore, in Chapter 3 entitled, “Methodology for unbalanced linguistic terms” we pro pose a newly constructed methodology to handle a set of unbalanced linguistic terms and further develop a novel 2-tuple linguistic technique for the unbalanced linguistic set. The new 2-tuple unbalanced linguistic model is computationally less complicated and can avoid information loss. Finally, numerical illustrations present the concrete steps of the developed approach and manifest the practicality and flexibility of this model by eluci dating a comparative analysis with existing models. The chapter is based on a research paper titled, “A New 2-Tuple Linguistic Approach for Unbalanced Linguistic Term Sets”, published in IEEE Transactions on Fuzzy Systems 29 (8) 2158–2168 (2021). Chapter 4 entitled, “Matrix games with probabilistic multiplicative unbalanced linguis tic information” proposes a novel concept of the probabilistic multiplicative unbalanced linguistic term set considering the probabilities as well as non-uniformity of distinct lin guistic labels. Further, based on the proposed concept a unified mechanism to solve a two-person linguistic matrix game having probabilistic multiplicative unbalanced linguis tic information is suggested. The proposed approach can be perceived as a convenient technique for multiple criteria decision-making (MCDM) problems. Numerical illustra tions are presented to discuss the significance of the proposed methodology. The chapter is based on a research paper titled, “Probabilistic multiplicative unbalanced linguistic term set and its application in matrix games”, communicated in International journal of ma chine learning and cybernetics, Springer. In Chapter 5 entitled, “Matrix games with interval-valued 2-tuple linguistic informa tion” a 2-player non-cooperative zero-sum interval-valued 2-tuple fuzzy linguistic (IVTFL) matrix game is proposed, and interval-valued linguistic linear programming (IVLLP) methodology is suggested to solve such class of games. A hypothetical example is used to demonstrate the suggested method’s applicability in the practical world. The chapter is based on a research paper titled, “Methodology for Interval-Valued Matrix Games with 2-Tuple Fuzzy Linguistic Information”, published in In: Sergeyev Y., Kvasov D. (eds) Numerical Computations: Theory and Algorithms. NUMTA 2019. Lecture Notes in xv Computer Science, Springer, Cham. , 11974, (2020). https://doi.org/10.1007/978-3-030- 40616-5_12. Chapter 6 entitled, “Interval norm approach for solving two player zero sum matrix games with interval payoffs” present a new approach that gives a unique outlook for solv ing a two-player zero-sum interval-valued matrix game (ZSIMG) based on the interval matrix norm framework. The methodology presented in this chapter helps obtain an ap proximated interval game value for the corresponding ZSIMG without undergoing the existing process of solving traditional interval linear mathematical models. The chapter is based on the research paper titled, “Interval norm approach for solving two-player zero sum matrix games with interval payoffs” Submitted in Computational optimization and application, Springer. After chapter 6, we present the summary of the research work carried out in this thesis. In addition, the future scope of the thesis has been discussed briefly.
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4

Ming-HsuanWu and 吳明璇. "Developing Intuitionistic 2-Tuple Fuzzy Linguistic Representation Models for Group Decision-Making Problems." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/30974453899275207084.

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Анотація:
碩士
國立成功大學
工業與資訊管理學系
104
The 2-tuple fuzzy linguistic representation models are considered to be a decision approach intended to calculate and aggregate linguistic evaluations without the loss of information. In current research, all linguistic terms are represented by triangular fuzzy numbers. However, if experts choose linguistic terms with different degrees of uncertainty, the triangular fuzzy numbers are not enough to represent the internally subjective evaluations of experts. As a result, this thesis uses the intuitionistic triangular fuzzy numbers to represent the linguistic terms in the intuitionistic linguistic term set. The intuitionistic triangular fuzzy numbers are composed of membership function, non-membership function and hesitancy information, expanding the information the linguistic terms contain. In a decision-making problem with multiple experts, the use of one linguistic term set may cause problems for some experts. To address these problems, this thesis develops the intuitionistic 2-tuple fuzzy linguistic representation models for group decision-making problems. The aim of this thesis is to consider that experts have different levels of uncertainty related to choosing linguistic terms and to allow them to use intuitionistic linguistic term sets with different granularity. The models consist of the following four stages: (1) We allow experts to use different intuitionistic linguistic term sets (ILTS) to obtain the linguistic preference values for each pair of alternatives. All the linguistic preference values are transformed into a specific linguistic term set, called the intuitionistic basic linguistic term set (IBLTS). Each linguistic preference value is expressed by means of an intuitionistic fuzzy set on the IBLTS, . (2) We use an aggregation operator for combining the intuitionistic fuzzy sets on the IBLTS to obtain the collective preference values for each pair of alternatives. (3) In this phase, we transform the intuitionistic fuzzy sets on the IBLTS into linguistic 2-tuple linguistic values over the IBLTS, a numerical value in the IBLTS granularity interval. (4) To facilitate the rank process, this phase uses a choice function to obtain the best alternative. This thesis looks forward to the use of intuitionistic linguistic term sets to express experts’ uncertainty in choosing linguistic terms and to convey more information in the internally subjective evaluations of experts. An example is used to demonstrate each step of our proposal models. Subsequently, the influence of both different order in which expert opinions are aggregated and different degrees of uncertainty among experts on the ranking results is analyzed.
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5

Wan-LingHsieh and 謝婉陵. "Applying 2-Tuple Fuzzy Linguistic Representation Model in Evaluating Preference of Group Decision Making." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/45826975052069614825.

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6

HUANG, BO-KAI, and 黃柏凱. "Developing the 2-tuple fuzzy linguistic model for supplier selection based on the customer requirements." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/qn6ghh.

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Анотація:
碩士
崑山科技大學
資訊管理研究所
104
Facing the globalization competition, supplier selection (SS) is an important decision making problem for the enterprise. The SS criteria (SSC) was replaced by consideration others criteria such as quality, process and delivery. Whether by the buyer’s view can conformity the downstream customer requirements (CRs), is to be discussed. In the literature, the fuzzy sets theory (FST) combined with others methods adopt to improve subjective judgment and fuzzy linguistic but the loss of information issue of FST. This study proposed a 2-tuple fuzzy linguistic approach by combining the analytic hierarchy process (AHP) to determine the weights of CRs. A 2-tuple fuzzy linguistic approach combining the Delphi method to filter SSC. A 2-tuple fuzzy linguistic approach combining the technique for order preference by similarity to ideal solution (TOPSIS) to arrange in order candidate suppliers. A 2-tuple fuzzy linguistic approach combining the quality function deployment (QFD) to determine the weights of SSC provide enterprise in accordance with SS. A vacuum coating device of semi-conductor industry case illustrates the applicability of the proposed approaches.
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7

Shiau, Ya-Wen, and 蕭雅文. "Constructing the risk assessing approach of failure modes and effects analysis method using 2-tuple fuzzy linguistic representation model." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/07634122576265573249.

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Анотація:
碩士
崑山科技大學
資訊管理研究所
100
The failure modes and effects analysis (FMEA) approach is used to solving the reliability and risk assessment problems for identifying potential failure mode of the system. Existing proposals for solving the risk assessment assume that all of the parameters in the same definition doamin including severity(S), occurrence (O) and detectability (D), consequently it raised the doubtful computational results. Fuzzy sets were introduced to improve this difficulty, the results cannot be guaranteed due to the reason that it may lose of information in the computational process. In this study, the 2-tuple fuzzy linguistic representation model is proposed to determine the assessments of S, O, D and obtain the more reasonable results of risk priority number (RPN) with OWGA (ordered weighted geometric averaging) operator. Delphi method is adopted for aggregating experts’ opinions in the group decision-making process. Finally, an example of cloud computing service is demonstrated to illustrate the applicability of the proposed approach to risk assessment.
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8

Nai-LunCheng and 鄭乃綸. "Aggregating Heterogeneous Information in Group Decision-Making Methods—Evaluating Product Design Factors by Intuitionistic Fuzzy Sets and 2-Tuple Fuzzy Linguistic Representations." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/86121490460257203564.

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9

Lin, Mei-Miao, and 林美妙. "Evaluation of Mobile Game Using AHP and 2-Tuples Linguistic Vaiables." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/74798953574049995692.

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Анотація:
碩士
大葉大學
資訊管理學系碩士在職專班
96
Long time ago, humankind kill their time by playing games.Different circumstances make different types of games and thus humankind could obtain satisfactions and pleasures. Games have this feature substantially and this is why people are very fond of playing games. Online games are quite different from mobile games. When people are playing games, they would be delighted due to several elements in those games. Facing with plenty fierce competitions of mobile games industry, dealers should draw up a proper management strategy and thus their products would successfully dominate the market. Under the competitive and indefinite circumstance, the market share would be raised if dealers could well aware of the players’ tendencies towards the products and could correspondingly develop. According to the case study in this thesis, managers could use “Analytical Hierarchy Process” (AHP) and “Linguistic Variable” to evaluate the market performance of mobile games. The competition’s status of mobile games could be described by using “Linguistic Variables.” As a result, the proposed model of the mobile games’ evaluation in this study is academically and valuable to discuss.
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10

Chiu, Wan-Yu, and 邱婉瑜. "Developing Fuzzy DSS for Selecting Principal of Senior High School Using the Operation of 2-Tuples Fuzzy Linguistic Label." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/14620714732693151630.

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Анотація:
碩士
國立雲林科技大學
資訊管理系碩士班
90
Abstract Currently, the selecting principal of senior high school has changed from assignment to selection. In this paper, our aims and contributions are: (1)Choice the criteria of selecting principal by surveying referenced literature. (2)Adopt questionnaire of fuzzy linguistic label to visit principals, teachers and education experts, and compare the three groups to get the difference between each other. (3)Use a new operation of 2-tuples fuzzy language label to calculate the weights of criteria and sub-criteria for principal candidates, and establish the algorithm of selecting principal. (4)In verification of selecting principal, by newly operation process, every school select 5 candidates in first stage exam; second stage take oral test by 15 experts. This paper illustrates an example from one senior high school to verify our proposed method. (5)In software system development, we use 2-tuples fuzzy linguistic label to develop fuzzy decision support system for selecting principal of senior high school. The developed DSS can support education institute and as a reference for selecting principal of senior high school.
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Книги з теми "2-TUPLE LINGUISTIC"

1

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. The 2-tuple Linguistic Model. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4.

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Herrera, Francisco, Luis Martínez, and Rosa M. Rodriguez. 2-Tuple Linguistic Model: Computing with Words in Decision Making. Springer International Publishing AG, 2015.

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3

Herrera, Francisco, Luis Martínez, and Rosa M. Rodriguez. 2-Tuple Linguistic Model: Computing with Words in Decision Making. Springer London, Limited, 2015.

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4

Herrera, Francisco, Luis Martínez, and Rosa M. Rodriguez. The 2-tuple Linguistic Model: Computing with Words in Decision Making. Springer, 2019.

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Частини книг з теми "2-TUPLE LINGUISTIC"

1

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "2-Tuple Linguistic Model." In The 2-tuple Linguistic Model, 23–42. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_2.

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2

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "Linguistic Approaches Based on the 2-Tuple Fuzzy Linguistic Representation Model." In The 2-tuple Linguistic Model, 43–50. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_3.

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3

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "Decision Making with Unbalanced Linguistic Information." In The 2-tuple Linguistic Model, 83–112. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_5.

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4

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "2-Tuple Linguistic Decision Based Applications." In The 2-tuple Linguistic Model, 131–43. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_7.

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5

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "Linguistic Decision Making and Computing with Words." In The 2-tuple Linguistic Model, 1–21. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_1.

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6

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "Flintstones: A Fuzzy Linguistic Decision Tools Enhancement Suite." In The 2-tuple Linguistic Model, 145–68. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_8.

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7

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "Decision Making in Heterogeneous Context: 2-Tuple Linguistic Based Approaches." In The 2-tuple Linguistic Model, 51–82. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_4.

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8

Martínez, Luis, Rosa M. Rodriguez, and Francisco Herrera. "Dealing with Hesitant Fuzzy Linguistic Information in Decision Making." In The 2-tuple Linguistic Model, 113–29. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24714-4_6.

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9

Pei, Zheng, Da Ruan, Jun Liu, and Yang Xu. "The 2-Tuple Fuzzy Linguistic Representation Model." In Linguistic Values Based Intelligent Information Processing: Theory, Methods, and Applications, 33–78. Paris: Atlantis Press, 2009. http://dx.doi.org/10.2991/978-94-91216-28-2_2.

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10

Labella, Álvaro, Bapi Dutta, Rosa M. Rodríguez, and Luis Martínez. "A Linguistic 2-tuple Best-Worst Method." In Lecture Notes in Operations Research, 41–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89795-6_4.

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Тези доповідей конференцій з теми "2-TUPLE LINGUISTIC"

1

Liu, Yi, Jun Liu, and Ya Qin. "Novel intuitionistic 2-tuple linguistic representation model." In Conference on Data Science and Knowledge Engineering for Sensing Decision Support (FLINS 2018). WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/9789813273238_0011.

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2

Liu, Pengsen, Hui Cui, Siyuan Luo, Hongyue Diao, and Li Zou. "Linguistic-Valued Lattice-Valued 2-Tuple Representation Model." In 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS). IEEE, 2018. http://dx.doi.org/10.1109/ccis.2018.8691396.

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3

TRUCK, ISIS, NESRIN HALOUANI, and SOUHAIL JEBALI. "LINGUISTIC NEGATION AND 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL: A NEW PROPOSAL." In Conference on Uncertainty Modelling in Knowledge Engineering and Decision Making (FLINS 2016). WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813146976_0016.

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4

Rodriguez, Rosa M., Luis Martinez, and Francisco Herrera. "A linguistic 2-tuple multicriteria decision making model dealing with hesitant linguistic information." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7338016.

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5

Hachicha, Raoudha Mkaouar, El Mouloudi Dafaoui, and Abderrahman El Mhamedi. "Competence evaluation approach based on 2-tuple linguistic representation model." In EM). IEEE, 2009. http://dx.doi.org/10.1109/icieem.2009.5344196.

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6

Matthews, Stephen G., Mario A. Gongora, Adrian A. Hopgood, and Samad Ahmadi. "Temporal fuzzy association rule mining with 2-tuple linguistic representation." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6251173.

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7

Li, Xinde, Xianzhong Dai, Jean Dezert, and Florentin Smarandache. "DSmT Qualitative Reasoning based on 2-Tuple Linguistic Representation Model." In 2008 9th International Conference for Young Computer Scientists (ICYCS). IEEE, 2008. http://dx.doi.org/10.1109/icycs.2008.219.

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8

Zhang, Xixiang, Jing Lei, and Baoan Yang. "Properties of Linguistic 2-tuple Judgement Matrix with Additive Consistency." In International Conference on Intelligent Systems and Knowledge Engineering 2007. Paris, France: Atlantis Press, 2007. http://dx.doi.org/10.2991/iske.2007.77.

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9

Wang, Haolun, and Ranjun Deng. "Approach of linguistic group decision making based on combination weighting 2-tuple linguistic VIKOR." In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407468.

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10

Gupta, Prashant K., and Pranab K. Muhuri. "Multi-objective linguistic optimization: Extensions and new directions using 2-tuple fuzzy linguistic representation model." In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2017. http://dx.doi.org/10.1109/fuzz-ieee.2017.8015772.

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