A new linguistic computational model based on discrete fuzzy numbers for computing with words

被引:170
|
作者
Massanet, Sebastia [1 ]
Riera, Juan Vicente [1 ]
Torrens, Joan [1 ]
Herrera-Viedma, Enrique [2 ]
机构
[1] Univ Balearic Isl, Dept Math & Comp Sci, Palma de Mallorca 07122, Spain
[2] Univ Granada, Dept Comp Sci & Artificial Intelligence, Granada, Spain
关键词
Discrete fuzzy number; Subjective evaluation; Multi-granular context; Aggregation function; AGGREGATION OPERATORS; REPRESENTATION MODEL; TERM SETS; SYSTEMS;
D O I
10.1016/j.ins.2013.06.055
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, several different linguistic computational models for dealing with linguistic information in processes of computing with words have been proposed. However, until now all of them rely on the special semantics of the linguistic terms, usually fuzzy numbers in the unit interval, and the linguistic aggregation operators are based on aggregation operators in [0,1]. In this paper, a linguistic computational model based on discrete fuzzy numbers whose support is a subset of consecutive natural numbers is presented ensuring the accuracy and consistency of the model. In this framework, no underlying membership functions are needed and several aggregation operators defined on the set of all discrete fuzzy numbers are presented. These aggregation operators are constructed from aggregation operators defined on a finite chain in accordance with the granularity of the linguistic term set. Finally, an example of a multi-expert decision-making problem in a hierarchical multi-granular linguistic context is given to illustrate the applicability of the proposed method and its advantages. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:277 / 290
页数:14
相关论文
共 50 条
  • [31] Evaluating the informative quality of documents in SGML format from judgements by means of fuzzy linguistic techniques based on computing with words
    Herrera-Viedma, E
    Peis, E
    INFORMATION PROCESSING & MANAGEMENT, 2003, 39 (02) : 233 - 249
  • [32] An approach to computing with words based on canonical characteristic values of linguistic labels
    Wang, Jin-Hsien
    Hao, Jongyun
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2007, 15 (04) : 593 - 604
  • [33] A New Bag of Words Model Based on Fuzzy Membership for Image Description
    Li Yanshan
    Xie Weixin
    Gao Zhijian
    Huang Qinghua
    Cao Yujie
    2014 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP), 2014, : 972 - 976
  • [34] On a total order on the set of Z-numbers based on discrete fuzzy numbers
    Mir-Fuentes, Arnau
    De Miguel, Laura
    Massanet, Sebastia
    Mir, Arnau
    Riera, Juan Vicente
    COMPUTATIONAL & APPLIED MATHEMATICS, 2024, 43 (05):
  • [35] A comparison of three approaches for estimating (synthesizing) an interval type-2 fuzzy set model of a linguistic term for computing with words
    Mendel, Jerry M.
    GRANULAR COMPUTING, 2016, 1 (01) : 59 - 69
  • [36] On the Aggregation of Zadeh's Z-Numbers Based on Discrete Fuzzy Numbers
    Massanet, Sebastia
    Vicente Riera, Juan
    Torrens, Joan
    AGGREGATION FUNCTIONS IN THEORY AND IN PRACTICE, 2018, 581 : 118 - 129
  • [37] A Method Adjusting Consistency and Consensus for Group Decision-Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers
    Zhao, Meng
    Liu, Ting
    Su, Jia
    Liu, Meng-Ying
    COMPLEXITY, 2018,
  • [38] A compensatory model for computing with words under discrete labels and incomplete information
    Cakir, Ozan
    KNOWLEDGE-BASED SYSTEMS, 2012, 27 : 29 - 37
  • [39] Fuzzy Query Processing Method based on Computing with Words Methodology
    Shamoi, Pakizar
    Inoue, Atsushi
    Akzhalova, Assel
    6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS, 2012, : 564 - 570
  • [40] Ranking discrete fuzzy linguistic performance based on TODIM method
    Chen S.
    Mo H.
    Pan D.
    Sadiq R.
    Deng Y.
    International Journal of System Assurance Engineering and Management, 2017, 8 (Suppl 4) : 2046 - 2050