Titlebook: Machine Learning Modeling for IoUT Networks; Internet of Underwat Ahmad A. Aziz El-Banna,Kaishun Wu Book 2021 The Author(s), under exclusiv

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Open Challenges for IoUT Networks,in underwater communication are as follows: the available datasets usually don’t provide complete parameters for proper training of the model, the proper selection of the ML model for the target problem, the complexity of some ML models when implemented on battery-based devices, and the applicabilit

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2191-5768 ater localization. They also discuss the current challenges of machine learning modeling of underwater communication from two communication engineering and data science perspectives..978-3-030-68566-9978-3-030-68567-6Series ISSN 2191-5768 Series E-ISSN 2191-5776

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,Seawater’s Key Physical Variables,while the second part is the “transport properties” like the electrical conductivity and viscosity [.]. In this chapter, we will discuss the key seawater’s physical variables that have direct and indirect impacts on the sound speed profile where a change in their values can lead to some changes in t

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ML: Modeling for Underwater Communication in IoUT Systems,unctions that adaptively exploit the wireless resources, optimize the network operation, and guarantee the QoS needs in real-time applications [., .]. Moreover, ML techniques extend their existence and are applied to underwater communication by employing many methods of classification and regression

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Open Challenges for IoUT Networks,dard underwater channel model (opposed to various empirical and analytical models for terrestrial channels) leads to more technical challenges. In this chapter, we examine the open challenges from the perspectives of both communication and data science..Some paradigms of the communication challenges

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ity as a plurality of mind-like immaterial beings and for whom physical bodies are ultimately unreal and our perceptions of them illusory. Re-reading the texts without the prior assumption of idealism allows the more material aspects of Leibniz‘s metaphysics to emerge. Leibniz is found to advance a