Multi-Objective Decision Making: Towards Improvement of Accuracy, Interpretability and Design Autonomy in Hierarchical Genetic Fuzzy Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{delgado:2002:FUZZIEEE,
  author =       "Myriam Regattieri Delgado and Fernando {Von Zuben} and 
                 Fernando Gomide",
  title =        "Multi-Objective Decision Making: Towards Improvement
                 of Accuracy, Interpretability and Design Autonomy in
                 Hierarchical Genetic Fuzzy Systems",
  booktitle =    "Proceedings of the 2002 IEEE International Conference
                 on Fuzzy Systems, FUZZ-IEEE-02",
  pages =        "1222--1227",
  year =         "2002",
  month =        "12-17 " # may,
  address =      "Hilton Hawaiian Village Hotel, Honolulu, Hawaii",
  publisher =    "IEEE Press",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  organisation = "IEEE",
  ISBN =         "0-7803-7280-8",
  keywords =     "genetic algorithms, genetic programming, accuracy,
                 classification problem, design autonomy, fitting, fuzzy
                 modelling, fuzzy models, generalisation, hierarchical
                 evolutionary process, hierarchical genetic fuzzy
                 systems, interpretability, interpretation
                 characteristics, multi-objective decision making,
                 single-objective epsiv, -constrained decision making
                 problems , decision theory, fuzzy systems, modelling,",
  DOI =          "doi:10.1109/FUZZ.2002.1006678",
  abstract =     "This paper presents fuzzy modeling as a
                 multi-objective decision making problem considering
                 accuracy, interpretability and autonomy as goals. The
                 proposed approach assumes that these goals can be
                 handled via corresponding single-objective
                 e-constrained decision making problems whose solution
                 is produced by a hierarchical evolutionary process. The
                 fitting, generalization, and interpretation
                 characteristics of the resulting fuzzy models are
                 discussed using a classification problem.",
  notes =        "IJCNN 2002 Held in connection with the World Congress
                 on Computational Intelligence (WCCI 2002)

                 The length of the chromosome, fixed by the constraint
                 e2, determines the maximum number of fuzzy rules but
                 smaller rule-bases are always aimed at first.",
}

Genetic Programming entries for Myriam Regattieri De Biase da Silva Delgado Fernando Jose Von Zuben Fernando Gomide

Citations