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| dc.contributor.author | FRATAVCHAN, Valerіi | |
| dc.contributor.author | FRATAVCHAN, Tonia | |
| dc.contributor.author | ABABII, Victor | |
| dc.date.accessioned | 2022-12-28T10:41:57Z | |
| dc.date.available | 2022-12-28T10:41:57Z | |
| dc.date.issued | 2022 | |
| dc.identifier.citation | FRATAVCHAN, Valerіi, FRATAVCHAN, Tonia, ABABII, Victor. Pseudo Genetic Algorithm of Clustering For Linear and Ellipsoidal Clusters. In: Electronics, Communications and Computing (IC ECCO-2022): 12th intern. conf., 20-21 Oct. 2022, Chişinău, Republica Moldova: conf. proc., Chişinău, 2022, pp. 183-185. | en_US |
| dc.identifier.uri | https://doi.org/10.52326/ic-ecco.2022/CS.07 | |
| dc.identifier.uri | http://repository.utm.md/handle/5014/21853 | |
| dc.description.abstract | This article considers the method of clustering in the problems of pattern recognition when studying with a teacher in the case of n-dimensional numerical features. Clusters of linear and ellipsoidal forms that are optimal in the number of errors are created by the method of pseudo genetic algorithm. The pseudo genetic algorithm has a simplified procedure for performing mutation and crossover operations. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Technical University of Moldova | en_US |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
| dc.subject | pattern recognition | en_US |
| dc.subject | clustering | en_US |
| dc.subject | numerical features | en_US |
| dc.subject | linear clusters | en_US |
| dc.subject | ellipsoidal clusters | en_US |
| dc.title | Pseudo Genetic Algorithm of Clustering For Linear and Ellipsoidal Clusters | en_US |
| dc.type | Article | en_US |
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2022
Proceedings of the 12th IC|ECCO; October 20-21, 2022
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