Using clustering methods to analyze sales of auto parts at a truck service station

Svetlana A. Evdokimova; Tatyana Novikova; Nataliya yakovenko

doi:10.12737/2219-0767-2023-16-4-23-32

UDC 004.89

USING CLUSTERING METHODS TO ANALYZE SALES OF AUTO PARTS AT A TRUCK SERVICE STATION Using clustering methods to analyze sales of auto parts at a truck service station

АА Аа

Published in Modeling of systems and processes · Volume 16, Issue 4 · Pages 23–32 · Rubric: Tehnicheskie nauki

DOI: https://doi.org/10.12737/2219-0767-2023-16-4-23-32

Received: 17.12.2023 Accepted: 20.12.2023 Published: 20.12.2023

Authors

Svetlana A. Evdokimova

Tatyana Novikova

Nataliya yakovenko

Svetlana A. Evdokimova

Academic degree: candidate of technical sciences

Voronezh State University of Forestry and Technologies named after G.F. Morozov Voronezh

Tatyana Novikova

Academic degree: candidate of technical sciences

Science rang: docent

Voronezh State University of Forestry and Technologies named after G.F. Morozov Associated professor · Chair of Computer Technology and Microelectronic Engineering · Voronezh

Nataliya yakovenko

Academic degree: candidate of technical sciences ; doctor of technical sciences ; doctor of technical sciences

Science rang: docent

Voronezh State University of Forestry and Technologies Voronezh

ABSTRACT

Clustering methods are widely used to divide goods into groups depending on sales volumes in order to build an optimal purchasing planning and inventory management strategy. Cluster analysis methods do not provide an unambiguous partition of the original set of objects, therefore, in the work, existing clustering methods were analyzed to study sales of auto parts at truck service stations. To solve the problem, the following methods were chosen: k-means, hierarchical agglomerative clustering and DBSCAN. Before using the k-means method, the elbow method found the optimal number of clusters. The DBSCAN method is based on object density and automatically determines the number of clusters. The initial data for cluster analysis was information on sales of spare parts at truck service stations for 3 years; clustering was applied to data by year. The DBSCAN algorithm showed unsatisfactory results, since most of the goods (86%) were identified in one cluster, while others contained units of goods. The k-means method gave the best partitioning result, each group has a different volume. The distribution of goods in clusters changes over three years, so managers should study the change in the affiliation of goods to one group or another. The obtained clustering results will help determine the real needs of spare parts at truck service stations and build an optimal procurement strategy.

KEYWORDS

Cluster analysis, Data Mining, k-means, DBSCAN, hierarchical agglomerative clustering, dendrogram, elbow method.

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Editor-in-Chief, editorial board chair

GOST

Evdokimova S. A., Novikova T. P., yakovenko N. V. Using clustering methods to analyze sales of auto parts at a truck service station // Modeling of systems and processes. 2023. no. 4. pp. 23-32. DOI: https://doi.org/10.12737/2219-0767-2023-16-4-23-32. (Date of access 19.09.2026).

MLA

Svetlana A. Evdokimova, Novikova T. P., yakovenko N. V.. "Using clustering methods to analyze sales of auto parts at a truck service station." Modeling of systems and processes 16.4 (2023): 23-32. DOI: https://doi.org/10.12737/2219-0767-2023-16-4-23-32.

APA

Evdokimova S. A., Novikova T. P., yakovenko N. V. (2023). Using clustering methods to analyze sales of auto parts at a truck service station. Modeling of systems and processes, 16(4), 23-32. https://doi.org/10.12737/2219-0767-2023-16-4-23-32

Chicago

Svetlana A. Evdokimova, Novikova T. P., yakovenko N. V.. "Using clustering methods to analyze sales of auto parts at a truck service station." Modeling of systems and processes 16, no. 4 (2023): 23-32. https://doi.org/10.12737/2219-0767-2023-16-4-23-32.

WIKI

{{cite journal | author = Evdokimova S. A., Novikova T. P., yakovenko N. V. | title = Using clustering methods to analyze sales of auto parts at a truck service station | journal = Modeling of systems and processes | year = 2023 | volume = 16 | issue = 4 | pages = 23-32 | doi = 10.12737/2219-0767-2023-16-4-23-32 }}

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USING CLUSTERING METHODS TO ANALYZE SALES OF AUTO PARTS AT A TRUCK SERVICE STATION Using clustering methods to analyze sales of auto parts at a truck service station

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