| DC Field | Value | Language |
|---|
| dc.contributor.author | Shafronenko, Alina | |
| dc.contributor.author | Bodyanskiy, Yevgeniy | |
| dc.contributor.author | Dolotov, Artem | |
| dc.contributor.author | Setlak, Galina | |
| dc.coverage.temporal | 21-25 August 2018, Lviv | |
| dc.date.accessioned | 2020-06-19T12:05:35Z | - |
| dc.date.available | 2020-06-19T12:05:35Z | - |
| dc.date.created | 2018-02-28 | |
| dc.date.issued | 2018-02-28 | |
| dc.identifier.citation | Fuzzy Clustering of Distorted Observations Based On Optimal Expansion Using Partial Distances / Alina Shafronenko, Yevgeniy Bodyanskiy, Artem Dolotov, Galina Setlak // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 327–330. — (Hybrid Systems of Computational Intelligence). | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/52516 | - |
| dc.description.abstract | The neural system that solves a problem of fuzzy
clustering of distorted observations based on optimal
expansion strategy using partial distance is proposed in this
article. To solve this problem we propose the learning
algorithm based on hybrid of rule “Winner-Takes-More” using
modified self-organizing neuro-fuzzy Kohonen network. This
modified system is characterized by basic characteristics, such
as: high speed, simple numerical realization, processing of
distorted information in online mode. | |
| dc.format.extent | 327-330 | |
| dc.language.iso | en | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 | |
| dc.subject | Kohonen self-organizing network | |
| dc.subject | fuzzy clustering | |
| dc.subject | incomplete observations with gaps | |
| dc.subject | partial distance | |
| dc.subject | optimal expansion | |
| dc.title | Fuzzy Clustering of Distorted Observations Based On Optimal Expansion Using Partial Distances | |
| dc.type | Conference Abstract | |
| dc.rights.holder | © Національний університет “Львівська політехніка”, 2018 | |
| dc.contributor.affiliation | Kharkiv National University of Radio Electronics | |
| dc.contributor.affiliation | Rzeszow University of Technology | |
| dc.format.pages | 4 | |
| dc.identifier.citationen | Fuzzy Clustering of Distorted Observations Based On Optimal Expansion Using Partial Distances / Alina Shafronenko, Yevgeniy Bodyanskiy, Artem Dolotov, Galina Setlak // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 327–330. — (Hybrid Systems of Computational Intelligence). | |
| dc.relation.references | [1] T Marwala, “Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques,” Hershey-New York: Information Science Reference, 2009. | |
| dc.relation.references | [2] J. C. Bezdek, “Pattern Recognition with Fuzzy Objective Function Algorithms,” Plenum Press, New York, 1981. | |
| dc.relation.references | [3] E. Lughofer, “Evolving Fuzzy Systems. Methodologies, Advanced Concepts and Applications,” Berlin-Hagenberg, 2011. | |
| dc.relation.references | [4] T. Kohonen, “Self-Organizing Maps,” Berlin: Springer-Verlag, 1995. | |
| dc.relation.references | [5] A. Y. Shafronenko, V. V. Volkova, and Ye. Bodyanskiy, “Adaptive clustering data with gaps,” Radioelectronics, informatics, control, no. 2. pp. 115-119, 2011. (in Russian) | |
| dc.relation.references | [6] Ye. Bodyanskiy, A. Shafronenko, and V. Volkova, “Аdaptive clustering of incomplete data using neuro-fuzzy Kohonen network. Artificial Intelligence Methods and Techniques for Business and Engineering Applications,” ITHEA, Rzeszow, Poland; Sofia, Bulgaria. pp. 287-296, 2012. | |
| dc.relation.references | [7] Ye. Bodyanskiy, A. Shafronenko, and V. Volkova, “Adaptive fuzzy probabilistic clustering of incomplete data,” Int. J. “Information, models and analyses”, vol.2, no. 2, pp. 112-117, 2013. | |
| dc.relation.references | [8] Ye. Bodyanskiy, А. Shafronenko, and V. Volkova, “Neuro fuzzy Kohonen network for incomplete data clustering using optimal completion strategy,” Proceedings 20th East West Fuzzy Colloquium 2013, Zittau, pp. 214-223, 25-27 September 2013. | |
| dc.relation.references | [9] V. Kolodyazhniy, Ye. Bodyanskiy and Ye. Gorshkov, “New recursive learning algorithms for fuzzy Kohonen clustering network,” Proc. 17th Int. Workshop on Nonlinear Dynamics of Electronc Systems, Rapperswil, Switzerland, pp. 58-61,, June 21-24, 2009. | |
| dc.relation.references | [10] R. J. Hathaway, and J. C Bezdek, “Fuzzy c-means clustering of incomplete data,”. IEEE Trans. on Systems, Man, and Cybernetics, vol. 31, no. 5, pp. 735-744, 2001. | |
| dc.relation.referencesen | [1] T Marwala, "Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques," Hershey-New York: Information Science Reference, 2009. | |
| dc.relation.referencesen | [2] J. C. Bezdek, "Pattern Recognition with Fuzzy Objective Function Algorithms," Plenum Press, New York, 1981. | |
| dc.relation.referencesen | [3] E. Lughofer, "Evolving Fuzzy Systems. Methodologies, Advanced Concepts and Applications," Berlin-Hagenberg, 2011. | |
| dc.relation.referencesen | [4] T. Kohonen, "Self-Organizing Maps," Berlin: Springer-Verlag, 1995. | |
| dc.relation.referencesen | [5] A. Y. Shafronenko, V. V. Volkova, and Ye. Bodyanskiy, "Adaptive clustering data with gaps," Radioelectronics, informatics, control, no. 2. pp. 115-119, 2011. (in Russian) | |
| dc.relation.referencesen | [6] Ye. Bodyanskiy, A. Shafronenko, and V. Volkova, "Adaptive clustering of incomplete data using neuro-fuzzy Kohonen network. Artificial Intelligence Methods and Techniques for Business and Engineering Applications," ITHEA, Rzeszow, Poland; Sofia, Bulgaria. pp. 287-296, 2012. | |
| dc.relation.referencesen | [7] Ye. Bodyanskiy, A. Shafronenko, and V. Volkova, "Adaptive fuzzy probabilistic clustering of incomplete data," Int. J. "Information, models and analyses", vol.2, no. 2, pp. 112-117, 2013. | |
| dc.relation.referencesen | [8] Ye. Bodyanskiy, A. Shafronenko, and V. Volkova, "Neuro fuzzy Kohonen network for incomplete data clustering using optimal completion strategy," Proceedings 20th East West Fuzzy Colloquium 2013, Zittau, pp. 214-223, 25-27 September 2013. | |
| dc.relation.referencesen | [9] V. Kolodyazhniy, Ye. Bodyanskiy and Ye. Gorshkov, "New recursive learning algorithms for fuzzy Kohonen clustering network," Proc. 17th Int. Workshop on Nonlinear Dynamics of Electronc Systems, Rapperswil, Switzerland, pp. 58-61,, June 21-24, 2009. | |
| dc.relation.referencesen | [10] R. J. Hathaway, and J. C Bezdek, "Fuzzy c-means clustering of incomplete data,". IEEE Trans. on Systems, Man, and Cybernetics, vol. 31, no. 5, pp. 735-744, 2001. | |
| dc.citation.conference | IEEE second international conference "Data stream mining and processing" | |
| dc.citation.spage | 327 | |
| dc.citation.epage | 330 | |
| dc.coverage.placename | Львів | |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference
|
