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NEURO-FUZZY MODEL OF THE INTENSITY OF TRANSMISSION OF INFORMATION FLOWS OVER A MULTISERVICE COMMUNICATION NETWORK

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Scientific Bulletin of Namangan State University

Scientific Bulletin of Namangan State University

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ARTICLE ANNOTATION

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In this article, an algorithm was created for choosing a 5-level architecture of a neuro-fuzzy model of a control system for a multiservice communication network and teaching its parameters. Algorithms for evaluating the effectiveness of control systems for multiservice networks have been developed.

AUTHORS

G.Sherboboyeva

Муҳаммад ал-Хоразмий номидаги Тошкент ахборот технологиялари университети Қарши филиали

Tags

# жадаллик# интенсивность# intensity# traffic# алгоритм обучения# learning algorithm# трафик# мультисервисли алоқа тармоғи# нейро-норавшан модел# таълуқлилик функцияси# ўқитиш алгорими# нейрон вазнлари# мультисервисная сеть связи# нейро-нечеткая модель# функция зависимости# веса нейронов# multiservice communication netwo# neuro-fuzzy model# dependence function# neuron weights

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Article Identifiers

ROI:

https://eroi.uz/11.0031/A0922-0020

DOI:

Not Available

References

Yusupbekov N.Yu, Marakhimov A.R, Sherboboyeva G.B., Marakhimov A. Implementation of Intelligent Technologies for Traffic Control Systems in the context of Megapolises // The 4th International Conference on BIG DATA APPLICATIONS AND SERVICES (BIGDAS2017). ISSN 2466-135X. Vol.4. №.1 Hosted by National University of Uzbekistan Korea Big Data Service Society August 15-18. 2017 Tashkent. pp. 281-289.

Siddikov I.X., Sherboboyeva G.B. Hybrid model management of information messages in multiservise networks // The advanced science journal, USA, 2014, Vol.2 pp.38-41.

Sherboboyeva G.B. Fuzzy modeling and multicriteria evaluation of the acceptability design solutions in the automated information system design // WCIS-2014. Тashkent. 2014. pp.458-463.