Fuzzy linear regression analysis

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  author =       "Jana Nowakova and Miroslav Pokorny",
  title =        "Fuzzy linear regression analysis",
  booktitle =    "12th IFAC Conference on Programmable Devices and
                 Embedded Systems, PDeS 2013",
  year =         "2013",
  volume =       "12",
  number =       "PART 1",
  pages =        "245--249",
  address =      "Velke Karlovice, Czech Republic",
  month =        "25-27 " # sep,
  publisher =    "FAC",
  keywords =     "genetic algorithms, genetic programming, Fuzzy model,
                 Fuzzy number, Genetic algorithms, Interval model,
                 Non-specificity, Possibility area, Regression model,
  DOI =          "doi:10.3182/20130925-3-CZ-3023.00079",
  URL =          "https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886731292&doi=10.3182%2f20130925-3-CZ-3023.00079&partnerID=40&md5=bfd4c3e76a489270babc1a4ce8db4805",
  affiliation =  "VSB-Technical University of Ostrava, Faculty of
                 Electrical Engineering and Computer Science, Department
                 of Cybernetics and Biomedical Engineering, 17.
                 listopadu 15/2172, 708 33 Ostrava Poruba, Czech
  abstract =     "The theoretical background for abstract formalization
                 of vague phenomenon of the complex systems is fuzzy set
                 theory. In the paper vague data as specialized fuzzy
                 sets - fuzzy numbers are defined and it is described a
                 fuzzy linear regression model as a fuzzy function with
                 fuzzy numbers as vague parameters. Interval and fuzzy
                 regression technologies are discussed, the linear fuzzy
                 regression model is proposed. To identify fuzzy
                 regression coefficients of model genetic algorithm is
                 applied. The numerical example is presented and the
                 possibility area of vague model is illustrated",
  source =       "Scopus",

Genetic Programming entries for Jana Nowakova Miroslav Pokorny