On the Optimization Models for Automatic Grouping of Industrial Products by Homogeneous Production Batches

Shkaberina, Guzel; Orlov, V. I.; Tovbis, Elena; Kazakovtsev, Lev

doi:10.1007/978-3-030-58657-7_33

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…2022), as well as from samples of industrial products (Kazakovtsev et al, 2015;Shkaberina et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Approach to Data Clustering Based on Molecular Chemical Reactions With Various Distance Measures

Markushin¹

2023

European Proceedings of Computers and Technology

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Automatic clustering involves dividing a set of objects into subsets so that the objects from one subset are more similar to each other than to the objects from other subsets according to some criterion. The paper proposes an algorithm for clustering data using the k-means algorithm combined with molecular chemical reactions and with various types of distance measures: Euclidean distance, Squared Euclidean distance, Manhattan distance. This approach mimics a chemical reaction process in which reactants interact with one another. Every chemical reaction process generate a new molecular structure in the environment. By molecular structure, we mean a possible solution to data clustering, by optimizing the molecular chemical reactions we mean optimizing the results of data clustering (search for a global optimal solution). The solution obtained with k-means is used as an initial molecular structure solution to optimize chemical reactions by generating new solutions: single-molecule collision, single-molecule decomposition, intermolecular collision, and intermolecular synthesis. Computational experiments demonstrate the comparative efficiency and accuracy of using the k-means algorithm combined with molecular chemical reactions.

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“…2022), as well as from samples of industrial products (Kazakovtsev et al, 2015;Shkaberina et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Approach to Data Clustering Based on Molecular Chemical Reactions With Various Distance Measures

Markushin¹

2023

European Proceedings of Computers and Technology

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Online clustering algorithm with a greedy agglomerative heuristic procedure and special distance measures

Shkaberina

Verenev

Tovbis

et al. 2023

Vii International Conference “Safety Problems of Civil Engineering Critical Infrastructures” (Spceci2021)

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Determination of the homogeneity of a set of elements on the basis of the quality characteristics of the division of a set into groups

Golovanov

Kazakovtsev

Shkaberina

2023

Vii International Conference “Safety Problems of Civil Engineering Critical Infrastructures” (Spceci2021)

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On the Optimization Models for Automatic Grouping of Industrial Products by Homogeneous Production Batches

Cited by 3 publications

References 24 publications

Approach to Data Clustering Based on Molecular Chemical Reactions With Various Distance Measures

Approach to Data Clustering Based on Molecular Chemical Reactions With Various Distance Measures

Online clustering algorithm with a greedy agglomerative heuristic procedure and special distance measures

Determination of the homogeneity of a set of elements on the basis of the quality characteristics of the division of a set into groups

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