Fuzzy linear regression analysis

Created by W.Langdon from gp-bibliography.bib Revision:1.7906

@InProceedings{Nowakova2013245,

• 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, Interval model, Non-specificity, Possibility area, Regression model, Vagueness",
• 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 Republic",
• 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

Citations