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Статті в журналах з теми "2-TUPLE LINGUISTIC"
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.
Повний текст джерелаWei, 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.
Повний текст джерелаAbdullah, 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.
Повний текст джерелаLiu, 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.
Повний текст джерелаShan, 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.
Повний текст джерелаZuo, 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.
Повний текст джерелаWang, 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.
Повний текст джерелаWang, 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.
Повний текст джерелаDeng, 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.
Повний текст джерелаNaz, 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.
Повний текст джерелаДисертації з теми "2-TUPLE LINGUISTIC"
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.
Повний текст джерелаYi-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.
Повний текст джерела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
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.
Повний текст джерелаMing-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.
Повний текст джерела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.
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.
Повний текст джерелаHUANG, 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.
Повний текст джерела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.
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.
Повний текст джерела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.
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.
Повний текст джерелаLin, 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.
Повний текст джерела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.
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.
Повний текст джерела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.
Книги з теми "2-TUPLE LINGUISTIC"
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.
Повний текст джерелаHerrera, Francisco, Luis Martínez, and Rosa M. Rodriguez. 2-Tuple Linguistic Model: Computing with Words in Decision Making. Springer International Publishing AG, 2015.
Знайти повний текст джерелаHerrera, Francisco, Luis Martínez, and Rosa M. Rodriguez. 2-Tuple Linguistic Model: Computing with Words in Decision Making. Springer London, Limited, 2015.
Знайти повний текст джерелаHerrera, Francisco, Luis Martínez, and Rosa M. Rodriguez. The 2-tuple Linguistic Model: Computing with Words in Decision Making. Springer, 2019.
Знайти повний текст джерелаЧастини книг з теми "2-TUPLE LINGUISTIC"
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.
Повний текст джерелаMartínez, 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.
Повний текст джерелаMartínez, 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.
Повний текст джерелаMartínez, 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.
Повний текст джерелаMartínez, 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.
Повний текст джерелаMartínez, 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.
Повний текст джерелаMartínez, 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.
Повний текст джерелаMartínez, 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.
Повний текст джерелаPei, 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.
Повний текст джерелаLabella, 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.
Повний текст джерелаТези доповідей конференцій з теми "2-TUPLE LINGUISTIC"
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.
Повний текст джерелаLiu, 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.
Повний текст джерелаTRUCK, 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.
Повний текст джерелаRodriguez, 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.
Повний текст джерелаHachicha, 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.
Повний текст джерелаMatthews, 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.
Повний текст джерелаLi, 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.
Повний текст джерелаZhang, 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.
Повний текст джерелаWang, 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.
Повний текст джерелаGupta, 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.
Повний текст джерела