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[HTML][HTML] A review on machine learning techniques for secured cyber-physical systems in smart grid networks
The smart grid (SG) is an advanced cyber-physical system (CPS) that integrates power grid
infrastructure with information and communication technologies (ICT). This integration …
infrastructure with information and communication technologies (ICT). This integration …
Machine learning for radio propagation modeling: a comprehensive survey
M Vasudevan, M Yuksel - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
With recent advancements in the telecommunication industry and the deployment of 5G
networks, radio propagation modeling is considered a fundamental task in planning and …
networks, radio propagation modeling is considered a fundamental task in planning and …
Machine learning with computer networks: Techniques, datasets and models
Machine learning has found many applications in network contexts. These include solving
optimisation problems and managing network operations. Conversely, networks are …
optimisation problems and managing network operations. Conversely, networks are …
Extremely randomized trees regressor scheme for mobile network coverage prediction and REM construction
CE García, I Koo - IEEE Access, 2023 - ieeexplore.ieee.org
In mobile communications network planning (and designing any radio system), coverage
prediction helps network operators optimize cellular networks to improve customer …
prediction helps network operators optimize cellular networks to improve customer …
Wetlinks: a large-scale longitudinal starlink dataset with contiguous weather data
Low Orbit Satellite (LEO) networks such as Starlink promise Internet access everywhere
around the world. In this paper, we present WetLinks-a large and publicly available trace …
around the world. In this paper, we present WetLinks-a large and publicly available trace …
A comprehensive guide to selecting suitable wavelet decomposition level and functions in discrete wavelet transform for fault detection in distribution networks
The paper presents a comprehensive analysis of the IEEE-16 bus system under different
operating conditions. It discusses the selection of suitable decomposition level and wavelet …
operating conditions. It discusses the selection of suitable decomposition level and wavelet …
[HTML][HTML] A comparative study of machine learning-based load balancing in high-speed train system
With the rapid developments of fifth generation (5G) mobile communication networks in
recent years, different use cases can now significantly benefit from 5G networks. One such …
recent years, different use cases can now significantly benefit from 5G networks. One such …
Machine learning-based online coverage estimator (MLOE): Advancing mobile network planning and optimization
Nowadays, the dependency on high-performance digital mobile connectivity is not limited to
human usage but also the intelligent objects increasingly deployed to serve the needs of …
human usage but also the intelligent objects increasingly deployed to serve the needs of …
Hyperparameter Optimization of Random Forest Algorithm to Enhance Performance Metric Evaluation of 5G Coverage Prediction
Utilizing of 5G technology has become a major focus in the development of more advanced
and efficient telecommunications networks. In this context, 5G coverage prediction becomes …
and efficient telecommunications networks. In this context, 5G coverage prediction becomes …
Comparative analysis of machine learning algorithms for 5G coverage prediction: identification of dominant feature parameters and prediction accuracy
H Yuliana - IEEE Access, 2024 - ieeexplore.ieee.org
5G technology is a key factor in delivering faster and more reliable wireless connectivity.
One crucial aspect in 5G network planning is coverage prediction, which enables network …
One crucial aspect in 5G network planning is coverage prediction, which enables network …