HYBRID APPROACH OF GMM AND K-MEANS METHODS IN OPTIMAL SEGMENTATION OF INDUSTRIAL INDUSTRIES
DOI:
https://doi.org/10.60078/3060-4842-2025-vol2-iss5-pp830-839Abstract
The article discusses the fact that segmentation in the optimization of industrial sectors is one of the current topical issues, and provides a comprehensive overview of the analytical reviews of the GMM model and K-means in segmentation. A comparative review of the K-Means and GMM methods in segmentation is fully analyzed. In the direction of the “Flowchart” of generalization of the GMM and K-means methods, the “New GMM Method” algorithm and the implementation algorithm of the Improved Hybrid Segmentation Model (HSM) are developed. Conclusions and suggestions are given on the hybrid approach to optimal segmentation of industrial sectors.
Keywords:
industrial sectors optimal segmentation clustering K-means method GMM (Gaussian Mixture Model) method Flowchart algorithm iteration adaptation integration covariance hybrid modelReferences
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