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HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey
Load forecasting is a vital part of smart grids for predicting the required electrical power
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
[PDF][PDF] Preserving Privacy of User Identity Based on Pseudonym Variable in 5G.
The fifth generation (5G) system is the forthcoming generation of the mobile communication
system. It has numerous additional features and offers an extensively high data rate, more …
system. It has numerous additional features and offers an extensively high data rate, more …
Quality of service-and fairness-aware resource allocation techniques for ieee802. 11ac WLAN
S Nosheen, JY Khan - IEEE Access, 2021 - ieeexplore.ieee.org
Increased demand for high-quality multimedia applications over IEEE802. 11 networks has
further motivated service providers to improve the QoS (quality of service) for all types of …
further motivated service providers to improve the QoS (quality of service) for all types of …
[HTML][HTML] Performance evaluation of congestion aware transmission opportunity scheduling scheme for 802.11 wireless LANs
DS Rao, VB Hency - International Journal of Intelligent Networks, 2021 - Elsevier
In the last two decades, Wireless Local Area Networks (WLANs) based on 802.11 have
become crucial in offering Internet services with high data transmission rates. Under …
become crucial in offering Internet services with high data transmission rates. Under …
Efficient models for enhancing the link adaptation performance of LTE/LTE-A networks
Link adaptation (LA) is the ability to adapt the modulation scheme (MS) and the coding rate
of the error correction in accordance with the quality of the radio link. The MS plays an …
of the error correction in accordance with the quality of the radio link. The MS plays an …
[PDF][PDF] HSIC bottleneck based distributed deep learning model for load forecasting in smart grid with a comprehensive survey
Load forecasting is a vital part of smart grids for predicting the required electrical power
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …
using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the …