Advertisement

Eurofuse 2011 pp 413-424 | Cite as

Towards a New Fuzzy Linguistic Preference Modeling Approach for Geolocation Applications

  • Mohammed-Amine Abchir
  • Isis Truck
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 107)

Abstract

In many areas, fuzzy linguistic approaches have already shown their interest and successful results to express the preferences and the choices of a human. This paper focuses on the fuzzy linguistic 2-tuple representation model that is interesting and relevant when we need to express and to refer to linguistic assessments during the whole reasoning process. However, when data have a particular distribution on their axis, this model doesn’t fit well the needs anymore. We propose therefore a variant version of this representation model that allow for a more realistic distribution. We also show that an operation such as an arithmetic mean is easy to implement with it and gives consistent results.

Keywords

Linguistic Term Fuzzy Partitioning Fuzzy Linguistic Approach Alert Type Linguistic Hierarchy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Gonzales, C., Perny, P., Queiroz, S.: GAI-Networks: Optimization, Ranking and Collective Choice in Combinatorial Domains. Foundations of computing and decision sciences 32(4), 3–24 (2008)MathSciNetGoogle Scholar
  2. 2.
    Boutilier, C., Brafman, R.I., Domshlak, C., Hoos, H.H., Poole, D.: CP-nets: A tool for representing and reasoning with conditional Ceteris Paribus Preference Statements. Journal of Artificial Intelligence Research 21, 135–191 (2004)MathSciNetzbMATHGoogle Scholar
  3. 3.
    Châtel, P., Truck, I., Malenfant, J.: LCP-nets: A linguistic approach for non-functional preferences in a semantic SOA environment. Journal of Universal Computer Science, 198–217 (2010)Google Scholar
  4. 4.
    Booth, P.: An Introduction to Human-Computer Interaction. Lawrence Erlbaum Associates, Publishers, USA (1989)Google Scholar
  5. 5.
    Ambriola, V., Gervasi, V.: Processing natural language requirements. In: International Conference on Automated Software Engineering, p. 36. IEEE Computer Society, USA (1997)Google Scholar
  6. 6.
    Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning, i, ii and iii. IS 8 (1975)Google Scholar
  7. 7.
    Herrera, F., Martínez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems 8(6), 746–752 (2000)CrossRefGoogle Scholar
  8. 8.
    Herrera, F., Martínez, L.: A model based on linguistic 2-tuples for dealing with multigranularity hierarchical linguistic contexts in multiexpert decisionmaking. IEEE Transactions on Systems, Man and Cybernetics. Part B: Cybernetics (2001)Google Scholar
  9. 9.
    Melekhova, O., Abchir, M.-A., Châtel, P., Malenfant, J., Truck, I., Pappa, A.: Self-Adaptation in Geotracking Applications: Challenges, Opportunities and Models. In: The 2nd International Conference on Adaptive and Self-Adaptive Systems and Applications (ADAPTIVE 2010), pp. 68–77. IEEE, Los Alamitos (2010)Google Scholar
  10. 10.
    Cengiz, S., Vedat, T., Fevzi Baba, A.: Pneumatic motor speed control by trajectory tracking fuzzy logic controller. Sadhana 35(1), 75–86 (2010)zbMATHCrossRefGoogle Scholar
  11. 11.
    Sung, W., You, K.: Adaptive precision geolocation algorithm with multiple model uncertainties. In: Adaptive Control, In-tech., pp. 323–336 (2009)Google Scholar
  12. 12.
    Zadeh, L.A.: Quantitative fuzzy semantics. Information Sciences 3(2), 159–176 (1971)MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Wang, J., Hao, J.: A new version of 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems 14(3), 435–445 (2006)CrossRefGoogle Scholar
  14. 14.
    Herrera, F., Herrera-viedma, E., Martínez, L.: A fuzzy linguistic methodology to deal with unbalanced linguistic term sets. IEEE Transactions on Fuzzy Systems, 354–370 (2008)Google Scholar
  15. 15.
    Cordón, O., Herrera, F., Zwir, I.: Linguistic modeling by hierarchical systems of linguistic rules. IEEE Transactions on Fuzzy Systems 10, 2–20 (2002)CrossRefGoogle Scholar
  16. 16.
    Herrera, F., Martínez, L.: A model based on linguistic 2-tuples for dealing with multigranularity hierarchical linguistic contexts in multiexpert decisionmaking. IEEE Transactions on Systems, Man and Cybernetics. Part B: Cybernetics, 227–234 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mohammed-Amine Abchir
    • 1
    • 2
  • Isis Truck
    • 1
  1. 1.Universite Paris 8Saint-DenisFrance
  2. 2.DeverywareParisFrance

Personalised recommendations