Jul 5, 2024 · Machine learning algorithm improve the coverage and connectivity of wireless sensor networks (WSNs) by optimizing the node placement, routing strategies and energy …

Jun 30, 2023 · Machine learning (ML) algorithms can manage the dynamic nature of WSNs better than traditionally programmed WSNs. ML is the process of self-learning from the experiences …

Machine learning algorithms present additional hurdles in terms of training and the amount of data required for training. This paper provides a convenient reference for wireless sensor network …

Apr 24, 2014 · In this paper, we present an extensive literature review over the period 2002–2013 of machine learning methods that were used to address common issues in WSNs. The …

In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks …

Sep 1, 2019 · In this survey, we present various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period …

different deep learning and machine learning algorithms and strategies in wireless networks. The paper [5] overviews common issues in wireless sensor networks (WSNs) and how they can be …

Nov 29, 2022 · Topics covered in this issue are categorized into the following six themes: (1) networking optimization, (2) unmanned aerial vehicle (UAV) applications, (3) wireless sensor …

Jun 23, 2022 · Machine learning algorithms present additional hurdles in terms of training and the amount of data required for training. This paper provides a convenient reference for wireless …

May 18, 2014 · In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor …