An empirical review of Machine Learning models for Energy Optimizations in IoT Networks-Reference-Cited by-同舟云学术

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An empirical review of Machine Learning models for Energy Optimizations in IoT Networks

Published:2023-07-06 Issue: Volume: Page:
ISSN:
Container-title:2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
language:
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Author:

Charde Pallavi¹,Lonkar Bhupesh B.²

Affiliation:

1. Faculty of Engineering and Technology,Department of Artificial Intelligence and Data Science,Sawangi, Wardha,India

2. Datta Meghe Institute of Engineering Technology & Research,Department of Information Technology,Sawangi, Wardha

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10306338/10306339/10307631.pdf?arnumber=10307631

Reference25 articles.

1. Mobility-Aware Offloading and Resource Allocation in a MEC-Enabled IoT Network With Energy Harvesting;qiu;IEEE Internet of Things Journal,2021

2. Parallel Route Optimization and Service Assurance in Energy-Efficient Software-Defined Industrial IoT Networks

3. An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms

4. Smart energy optimization for massive IoT using artificial intelligence;raval;Internet of Things,2021

5. Toward Energy-Oriented Optimization for Green Communication in Sensor Enabled IoT Environments

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Pragmatic Review of QoS Optimisations in IoT Driven Networks;Wireless Personal Communications;2024-07

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