HYBRID APPROACH OF GMM AND K-MEANS METHODS IN OPTIMAL SEGMENTATION OF INDUSTRIAL INDUSTRIES

Rakhimov, Anvar, Рахимов, Анвар, Raximov, Anvar

Илғор иқтисодиёт ва педагогик технологиялар · 2025-yil

Annotatsiya

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.

Maqola ma’lumotlari
MualliflarRakhimov, Anvar, Рахимов, Анвар, Raximov, Anvar
JurnalИлғор иқтисодиёт ва педагогик технологиялар
Nashr sanasi2025-11-04
Jild2
Son5
Betlar830-839
TilO‘zbek
DOI10.60078/3060-4842-2025-vol2-iss5-pp830-839

Kalit so‘zlar

industrial sectors, optimal, segmentation, clustering, K-means method, GMM (Gaussian Mixture Model) method, Flowchart, algorithm, iteration, adaptation, integration, covariance, hybrid model, промышленные отрасли, оптимальный, сегментация, кластеризация, метод K-средних, метод GMM (модель смеси Гаусса), блок-схема, алгоритм, итерация, адаптация, интеграция, ковариация, гибридная модель, sanoat tarmoqlari, optimal, segmentatsiyalash, klasterlashtirish, K-means usuli, GMM (Gaussian Mixture Model) usuli, Oqim sxemasi, algoritm, iteratsiya, adaptatsiya, integratsiya, kovariatsiya, gibrid model

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