Machine learning in beyond 5G/6G networks—State-of-the-art and future trends
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
Point-to-point communication in integrated satellite-aerial 6G networks: State-of-the-art and future challenges
This paper surveys the literature on point-to-point (P2P) links for integrated satellite-aerial
networks, which are envisioned to be among the key enablers of the sixth-generation (6G) of …
networks, which are envisioned to be among the key enablers of the sixth-generation (6G) of …
A comparative performance of machine learning algorithm to predict electric vehicles energy consumption: A path towards sustainability
The rapid growth of transportation sector and related emissions are attracting the attention of
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …
A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms
R Rajamoorthy, G Arunachalam… - Energy Sources, Part …, 2022 - Taylor & Francis
ABSTRACT Intelligent Transport System (ITS) intentions to attain traffic efficiency by
diminishing traffic difficulties. It supplies information like traffic issues, real-time traveling …
diminishing traffic difficulties. It supplies information like traffic issues, real-time traveling …
Computational complexity evaluation of neural network applications in signal processing
In this paper, we provide a systematic approach for assessing and comparing the
computational complexity of neural network layers in digital signal processing. We provide …
computational complexity of neural network layers in digital signal processing. We provide …
[HTML][HTML] Artificial intelligence for trusted autonomous satellite operations
Abstract Recent advances in Artificial Intelligence (AI) and Cyber-Physical Systems (CPS)
for aerospace applications have brought about new opportunities for the fast-growing …
for aerospace applications have brought about new opportunities for the fast-growing …
Computational complexity optimization of neural network-based equalizers in digital signal processing: a comprehensive approach
P Freire, S Srivallapanondh, B Spinnler… - Journal of Lightwave …, 2024 - ieeexplore.ieee.org
Experimental results based on offline processing reported at optical conferences
increasingly rely on neural network-based equalizers for accurate data recovery. However …
increasingly rely on neural network-based equalizers for accurate data recovery. However …
Artificial intelligence for satellite communication and non-terrestrial networks: A survey
This paper surveys the application and development of Artificial Intelligence (AI) in Satellite
Communication (SatCom) and Non-Terrestrial Networks (NTN). We first present a …
Communication (SatCom) and Non-Terrestrial Networks (NTN). We first present a …
Deep reinforcement learning for microstructural optimisation of silica aerogels
Silica aerogels are being extensively studied for aerospace and transportation applications
due to their diverse multifunctional properties. While their microstructural features dictate …
due to their diverse multifunctional properties. While their microstructural features dictate …
Deep conviction systems for biomedical applications using intuiting procedures with cross point approach
H Manoharan, S Selvarajan, A Yafoz… - Frontiers in Public …, 2022 - frontiersin.org
The production, testing, and processing of signals without any interpretation is a crucial task
with time scale periods in today's biological applications. As a result, the proposed work …
with time scale periods in today's biological applications. As a result, the proposed work …