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Clustering Algorithm with a Greedy Agglomerative Heuristic and Special Distance Measures

Описание

Тип публикации: статья из журнала

Год издания: 2022

Идентификатор DOI: 10.3390/a15060191

Ключевые слова: clustering, greedy agglomerative heuristic, kohonen neural network, self-organized kohonen map

Аннотация: Automatic grouping (clustering) involves dividing a set of objects into subsets (groups) so that the objects from one subset are more similar to each other than to the objects from other subsets according to some criterion. Kohonen neural networks are a class of artificial neural networks, the main element of which is a layer of adПоказать полностьюaptive linear adders, operating on the principle of “winner takes all”. One of the advantages of Kohonen networks is their ability of online clustering. Greedy agglomerative procedures in clustering consistently improve the result in some neighborhood of a known solution, choosing as the next solution the option that provides the least increase in the objective function. Algorithms using the agglomerative greedy heuristics demonstrate precise and stable results for a k-means model. In our study, we propose a greedy agglomerative heuristic algorithm based on a Kohonen neural network with distance measure variations to cluster industrial products. Computational experiments demonstrate the comparative efficiency and accuracy of using the greedy agglomerative heuristic in the problem of grouping of industrial products into homogeneous production batches. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

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Издание

Журнал: Algorithms

Выпуск журнала: Vol. 15, Is. 6

Номера страниц: 191

ISSN журнала: 19994893

Издатель: MDPI

Персоны

  • Shkaberina G. (Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation)
  • Verenev L. (Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation)
  • Tovbis E. (Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation)
  • Rezova N. (Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation)
  • Kazakovtsev L. (Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky Rabochy Av., Krasnoyarsk, 660037, Russian Federation, Institute of Business Process Management, Siberian Federal University, 79 Svobodny Av., Krasnoyarsk, 660041, Russian Federation)

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