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Titlebook: Computer Networks and Inventive Communication Technologies; Proceedings of Third S. Smys,Ram Palanisamy,Grigorios N. Beligiannis Conference

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發(fā)表于 2025-3-21 16:04:23 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Computer Networks and Inventive Communication Technologies
副標(biāo)題Proceedings of Third
編輯S. Smys,Ram Palanisamy,Grigorios N. Beligiannis
視頻videohttp://file.papertrans.cn/234/233662/233662.mp4
概述Presents research works in the field of computer networks and data communications.Discusses results of ICCNCT 2020 held in Coimbatore, India, during 23–24 July 2020.Serves as a reference for researche
叢書(shū)名稱Lecture Notes on Data Engineering and Communications Technologies
圖書(shū)封面Titlebook: Computer Networks and Inventive Communication Technologies; Proceedings of Third S. Smys,Ram Palanisamy,Grigorios N. Beligiannis Conference
描述.This book is a collection of peer-reviewed best selected research papers presented at 3rd International Conference on Computer Networks and Inventive Communication Technologies (ICCNCT 2020). The book covers new results in theory, methodology, and applications of computer networks and data communications. It includes original papers on computer networks, network protocols and wireless networks, data communication technologies, and network security. The proceedings of this conference is a valuable resource, dealing with both the important core and the specialized issues in the areas of next generation wireless network design, control, and management, as well as in the areas of protection, assurance, and trust in information security practice. It is a reference for researchers, instructors, students, scientists, engineers, managers, and industry practitioners for advance work in the area..
出版日期Conference proceedings 2021
關(guān)鍵詞ICCNCT 2020; ICCNCT Proceedings; Wireless Communication; Optical Communication; Computer Networks; Networ
版次1
doihttps://doi.org/10.1007/978-981-15-9647-6
isbn_softcover978-981-15-9649-0
isbn_ebook978-981-15-9647-6Series ISSN 2367-4512 Series E-ISSN 2367-4520
issn_series 2367-4512
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Comparative Study of Machine Learning Techniques for Chronic Disease Prognosis, the general focus is to predict a single disease using dataset and methods appropriate only for that disease. A comparative study of machine learning algorithms is proposed for the effective prognosis of five major chronic diseases using behavioral risk factors through a single dataset. The logisti
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