Multivariate data approximation with preprocessing of data
Abstract
An adaptive information system is constructed in order to approximate a set of multidimensional data. To get better approximation properties a pre-processing stage of data is proposed in which the set of points, forming the multidimensional data base and called a training set TRE, undergoes a clustering analysis. In the analysis two independent clustering algorithms are used; on each cluster a feed-forward neural network is trained and a membership function of a fuzzy set is constructed. The constructed system contains a module of two-conditional fuzzy rules consequent parts of which are of the functional type. Each rule is designed on a pair of clusters.
Keywords
References
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Published
Aug 17, 2022
How to Cite
KOSIŃSKI, Witold; KOWALCZYK, Dorota; WEIGL, Martyna.
Multivariate data approximation with preprocessing of data.
Computer Assisted Methods in Engineering and Science, [S.l.], v. 14, n. 4, p. 651-658, aug. 2022.
ISSN 2956-5839.
Available at: <https://cames.ippt.gov.pl/index.php/cames/article/view/798>. Date accessed: 13 nov. 2024.
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