GH-VNS-based algorithms for clustering problem : монография

Rozhnov I.P.; Kazakovtsev L.A.; Karaseva M.V.

Дополнительные ссылки: eLibrary

База данных: Каталог библиотеки СФУ

Библиографическое описание: GH-VNS-based algorithms for clustering problem : монография / I. P. Rozhnov, L. A. Kazakovtsev, M. V. Karaseva. - Moscow : [s. n.], 2024. - 162 p. - ISBN 9785160196053 : Б. ц. - Текст : непосредственный.

Аннотация: A problem of increasing the accuracy and stability of the automatic grouping (clus-tering) algorithms is considered based on a new approach to developing clustering al-gorithms based on parametric optimization models for k-means, k-medoid, clear clus-tering problems based on separation of a mixture of probability distributions (with ap-plication of the classification EM-algorithm). The study proposes new search algo-rithms with alternating randomized neighborhoods and parallel modifications of algo-rithms with a greedy agglomerative heuristic procedure for large automatic grouping problems, adapted to the CUDA architecture. Moreover, the study presents a procedure for composing optimal ensembles of automatic grouping algorithms with a combined application of the genetic algorithm of the greedy heuristic method and a consistent matrix of binary partitions for practical problems. Algorithms and procedure for com-posing optimal ensembles are implemented to solve the problem of dividing prefabri-cated lots of industrial products into homogeneous lots based on the results of non-destructive tests. The work is intended for scientists, specialists, undergraduate and postgraduate stu-dents involved in the development of cluster analysis algorithms, as well as in improv-ing the quality of industrial products.

Год издания: 2024

Авторы: Rozhnov I.P. , Kazakovtsev L.A. , Karaseva M.V.

Издательство: Moscow

Количество страниц: 162

Держатель оригинала документа: Siberian Federal University

Количество экземпляров:

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