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Intelligent Optimization Framework for Future Communication Networks using Machine Learning

By
Vijaya Saradhi Thommandru ,
Vijaya Saradhi Thommandru

Department of Computer Science and Engineering, School of Technology ,GITAM (Deemed to be University), Hyderabad, India

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T. Suma ,
T. Suma

Department of Computer Science and Engineering, Sri Venkateshwara College of Engineering, Bengaluru, India

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A. Mary Odilya Teena ,
A. Mary Odilya Teena

PG Department of Computer Applications, St. Joseph's College of Arts and Science (Autonomous), Cuddalore, Tamil Nadu, India

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A. Muthukrishnan ,
A. Muthukrishnan

Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, Tamilnadu, India

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P Thamaraikannan ,
P Thamaraikannan

Department of Information Technology, Adithya Institute of Technology, Coimbatore, Tamil Nadu, India

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S. Manikandan ,
S. Manikandan

Department of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, India

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Abstract

Confronting the undeniably complicated versatile correspondence organization, knowledge is the advancement heading of organization versatile improvement innovation later on. Portable correspondence information is a significant part representing things to come data society. AI calculation is embraced in the versatile improvement plot, which can facilitate different enhancement goals as per the progressions of climate and state and understand the ideal boundary arrangement. Canny portable terminal hardware is turning out to be increasingly well known. The combination and advancement of social, portable and area administrations make the conventional informal organization easily change to versatile correspondence organization. AI is a part of man-made consciousness. Its examination objective is to construct a framework which can advance a few guidelines from information and apply them to the resulting information handling. In light of chart hypothesis, this paper tackles the issue of correspondence network information really, and concentrates on the calculation of huge information examination in view of AI.

How to Cite

1.
Saradhi Thommandru V, Suma T, Odilya Teena AM, Muthukrishnan A, Thamaraikannan P, Manikandan S. Intelligent Optimization Framework for Future Communication Networks using Machine Learning. Data and Metadata [Internet]. 2024 Apr. 29 [cited 2024 May 24];3:277. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/277

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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