| 書目名稱 | Machine Learning Modeling for IoUT Networks |
| 副標題 | Internet of Underwat |
| 編輯 | Ahmad A. Aziz El-Banna,Kaishun Wu |
| 視頻video | http://file.papertrans.cn/621/620409/620409.mp4 |
| 概述 | Presents the basics of the Internet of Underwater Things (IoUT) architecture and underwater transmission.Includes applications of machine learning techniques for underwater communication.Features open |
| 叢書名稱 | SpringerBriefs in Computer Science |
| 圖書封面 |  |
| 描述 | This book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments, known as .Internet of Underwater. .Things. (IoUT). The authors first present seawater’s key physical variables and go on to discuss opportunistic transmission, localization and positioning, machine learning modeling for underwater communication, and ongoing challenges in the field. In addition, the authors present applications of machine learning techniques for opportunistic communication and underwater localization. They also discuss the current challenges of machine learning modeling of underwater communication from two communication engineering and data science perspectives.. |
| 出版日期 | Book 2021 |
| 關(guān)鍵詞 | Underwater communication; underwater sensor networks; underwater localization; underwater positioning; I |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-68567-6 |
| isbn_softcover | 978-3-030-68566-9 |
| isbn_ebook | 978-3-030-68567-6Series ISSN 2191-5768 Series E-ISSN 2191-5776 |
| issn_series | 2191-5768 |
| copyright | The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 |
|Archiver|手機版|小黑屋|
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