skip to main content
research-article

On fuzzy-qualitative descriptions and entropy

Published: 01 August 2016 Publication History

Abstract

This paper models the assessments of a group of experts when evaluating different magnitudes, features or objects by using linguistic descriptions. A new general representation of linguistic descriptions is provided by unifying ordinal and fuzzy perspectives. Fuzzy-qualitative labels are proposed as a generalization of the concept of qualitative labels over a well-ordered set. A lattice structure is established in the set of fuzzy-qualitative labels to enable the introduction of fuzzy-qualitative descriptions as L-fuzzy sets. A theorem is given that characterizes finite fuzzy partitions using fuzzy-qualitative labels, the cores and supports of which are qualitative labels. This theorem leads to a mathematical justification for commonly-used fuzzy partitions of real intervals via trapezoidal fuzzy sets. The information of a fuzzy-qualitative label is defined using a measure of specificity, in order to introduce the entropy of fuzzy-qualitative descriptions. A new general representation of linguistic descriptions by unifying ordinal and fuzzy perspectives.The construction of the extended set of fuzzy-qualitative labels over a well-ordered set.A theorem characterizing commonly-used fuzzy partitions of real intervals via trapezoidal fuzzy sets.The definition of the fuzzy-qualitative descriptions of a set as L-fuzzy sets, and the proof of its lattice structure.The entropy of a fuzzy-qualitative description providing a unified framework for the discrete and continuous cases.

References

[1]
P. Burillo, H. Bustince, Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets, Fuzzy Sets Syst., 78 (1996) 305-316.
[2]
I. Couso, D. Dubois, Statistical reasoning with set-valued information: ontic vs. epistemic views, Int. J. Approx. Reason., 55 (2014) 1502-1518.
[3]
G. Deschrijver, E.E. Kerre, On the relationship between some extensions of fuzzy set theory, Fuzzy Sets Syst., 133 (2003) 227-235.
[4]
D. Dubois, H. Prade, Gradualness, uncertainty and bipolarity: making sense of fuzzy sets, Fuzzy Sets Syst., 192 (2012) 3-24.
[5]
M. Espinilla, J. Liu, L. Martínez, An extended hierarchical linguistic model for decision-making problems, Comput. Intell., 27 (2011) 489-512.
[6]
F.J. Estrella, M. Espinilla, F. Herrera, L. Martínez, FLINTSTONES: a fuzzy linguistic decision tools enhancement suite based on the 2-tuple linguistic model and extensions, Inf. Sci., 280 (2014) 152-170.
[7]
B. Farhadinia, Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets, Inf. Sci., 240 (2013) 129-144.
[8]
L. Garmendia, The evolution of the concept of fuzzy measure, in: Studies in Computational Intelligence, vol. 5, 2005, pp. 185-200.
[9]
S. Greenfield, F. Chiclana, Accuracy and complexity evaluation of defuzzification strategies for the discretised interval type-2 fuzzy set, Int. J. Approx. Reason., 54 (2013) 1013-1033.
[10]
F. Herrera, E. Herrera-Viedma, L. Martínez, A fuzzy linguistic methodology to deal with unbalanced linguistic term sets, IEEE Trans. Fuzzy Syst., 16 (2008) 354-370.
[11]
F. Herrera, S. Alonso, F. Chiclana, E. Herrera-Viedma, Computing with words in decision making: foundations, trends and prospects, Fuzzy Optim. Decis. Mak., 8 (2009) 337-364.
[12]
M. Kwiatkowska, K. Kielan, Fuzzy logic and semiotic methods in modeling of medical concepts, Fuzzy Sets Syst., 214 (2013) 35-50.
[13]
F. Liu, J.M. Mendel, Encoding words into interval type-2 fuzzy sets using an interval approach, IEEE Trans. Fuzzy Syst., 16 (2008) 1503-1521.
[14]
J.M. Mendel, H. Wu, Type-2 fuzzistics for symmetric interval type-2 fuzzy sets: part 1, forward problems, IEEE Trans. Fuzzy Syst., 14 (2006) 781-792.
[15]
L. Meng, X. Wang, E. Kerre, An improved representation theorem of L-fuzzy sets, Fuzzy Sets Syst., 161 (2010) 3141-3147.
[16]
C.-H. Nguyen, V.N. Huynh, W. Pedrycz, A construction of sound semantic linguistic scales using 4-tuple representation of term semantics, Int. J. Approx. Reason., 55 (2014) 763-786.
[17]
R.O. Parreiras, P. Ya. Ekel, J.S.C. Martini, R.M. Palhares, A flexible consensus scheme for multicriteria group decision making under linguistic assessments, Inf. Sci., 180 (2010) 1075-1089.
[18]
P. Pérez-Asurmendi, F. Chiclana, Linguistic majorities with difference in support, Appl. Soft Comput., 18 (2014) 196-208.
[19]
C. Porcel, A. Tejeda-Lorente, M.A. Martínez, E. Herrera-Viedma, A hybrid recommender system for the selective dissemination of research resources in a technology transfer office, Inf. Sci., 184 (2012) 1-19.
[20]
F. Prats, L. Roselló, M. Sánchez, N. Agell, Using L-fuzzy sets to introduce information theory into qualitative reasoning, Fuzzy Sets Syst., 236 (2014) 73-90.
[21]
R.M. Rodriguez, L. Martínez, F. Herrera, Hesitant fuzzy linguistic term sets for decision making, IEEE Trans. Fuzzy Syst., 20 (2012) 109-119.
[22]
L. Roselló, F. Prats, N. Agell, M. Sánchez, Measuring consensus in group decisions by means of qualitative reasoning, Int. J. Approx. Reason., 51 (2010) 441-452.
[23]
E. Szmidt, J. Kacprzyk, Entropy for intuitionistic fuzzy sets, Fuzzy Sets Syst., 118 (2001) 467-477.
[24]
V. Torra, Hesitant fuzzy sets, Int. J. Intell. Syst., 25 (2010) 529-539.
[25]
L. Travé-Massuyès, P. Dague, L. Ironi, Mathematical foundations of qualitative reasoning, AI Mag., 24 (2003) 91-106.
[26]
L. Travé-Massuyès, F. Prats, M. Sánchez, N. Agell, Relative and absolute order-of-magnitude models unified, Ann. Math. Artif. Intell., 45 (2005) 323-341.
[27]
D. Wu, J.M. Mendel, Uncertainty measures for interval type-2 fuzzy sets, Inf. Sci., 177 (2007) 5378-5393.
[28]
M. Xia, Z. Xu, Hesitant fuzzy information aggregation in decision making, Int. J. Approx. Reason., 52 (2011) 395-407.
[29]
R.R. Yager, Measures of specificity, Comput. Syst. Sci., 162 (1996) 94-113.
[30]
W. Zeng, H. Li, Relationship between similarity measure and entropy of interval valued fuzzy sets, Fuzzy Sets Syst., 157 (2006) 1477-1484.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image International Journal of Approximate Reasoning
International Journal of Approximate Reasoning  Volume 75, Issue C
August 2016
108 pages

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 August 2016

Author Tags

  1. Fuzzy partitions
  2. Information sciences
  3. L-fuzzy sets
  4. Measures of information
  5. Qualitative reasoning

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 13 Jan 2025

Other Metrics

Citations

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media