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.
| Mualliflar | Rakhimov, Anvar, Рахимов, Анвар, Raximov, Anvar |
|---|---|
| Jurnal | Илғор иқтисодиёт ва педагогик технологиялар |
| Nashr sanasi | 2025-11-04 |
| Jild | 2 |
| Son | 5 |
| Betlar | 830-839 |
| Til | O‘zbek |
| DOI | 10.60078/3060-4842-2025-vol2-iss5-pp830-839 |
DOI: 10.60078/3060-4842-2025-vol2-iss5-pp830-839 · Maqolaning asl sahifasi
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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