On multidimensional linear modelling including real uncertainty

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Article{Nowakova2014511,

• author = "Jana Nowakova and Miroslav Pokorny",
• title = "On multidimensional linear modelling including real uncertainty",
• journal = "Advances in Electrical and Electronic Engineering",
• year = "2014",
• volume = "12",
• number = "5",
• pages = "511--517",
• keywords = "genetic algorithms, genetic programming, Complex systems, Fuzzy linear regression, Fuzzy number, Fuzzy set, Possibility area, Vague property",
• broken = "https://www.scopus.com/inward/record.uri?eid=2-s2.0-84920135016&doi=10.15598%2faeee.v12i5.1143&partnerID=40&md5=219d3cbd0311aedc8f8beb1348e0911d",
• DOI = "doi:10.15598/aeee.v12i5.1143",
• affiliation = "Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, 17. listopadu 15/2172, Ostrava-Poruba, Czech Republic",
• abstract = "The theoretical background for abstract for-malization of vague phenomenon of complex systems is fuzzy set theory. In the paper are defined vague data as specialized fuzzy sets - fuzzy numbers and there is described a fuzzy linear regression model as a fuzzy function with fuzzy numbers as vague regression parameters. To identify the fuzzy coefficients of model the genetic algorithm is used. The linear approximation of vague function together with its possibility area are analytically and graphically expressed. The suitable numerical experiments are performed namely in the task of two-dimensional fuzzy function modelling and the time series fuzzy regression analysis as well.",
• source = "Scopus",

}

Genetic Programming entries for Jana Nowakova Miroslav Pokorny

Citations