M Khani, S Jamali, MK Sohrabi… - Transactions on …, 2024 - Wiley Online Library
This paper reviews recent research on resource allocation in 5G cloud‐based radio access networks (C‐RAN) using deep reinforcement learning (DRL) algorithms. It explores the …
X Zhou, W Lin, R Kumar, P Cui, Z Ma - Applied Energy, 2022 - Elsevier
Data-driven modeling emerges as a promising approach to predicting building electricity consumption and facilitating building energy management. However, the majority of the …
F Dakalbab, MA Talib, Q Nassir, T Ishak - Journal of King Saud University …, 2024 - Elsevier
Artificial Intelligence (AI) approaches have been increasingly used in financial markets as technology advances. In this research paper, we conduct a Systematic Literature Review …
Vehicle control in autonomous traffic flow is often handled using the best decision-making reinforcement learning methods. However, unexpected critical situations make the collisions …
Finding a more efficient trading strategy has always been one of the main concerns in financial market trading. In order to create trading strategies that lead to higher profits …
L Song, D Li, X Wang, X Xu - Information Sciences, 2022 - Elsevier
Studying the representational capacity of neural networks to learn nonlinear rewards is necessary in a complex and nonlinear environment. Over recent years, the maximum …
In the evolving landscape of portfolio management (PM), the fusion of advanced machine learning techniques with traditional financial methodologies has opened new avenues for …
G Mattera, R Mattera - Intelligent Systems with Applications, 2023 - Elsevier
A large amount of assets characterizes high-dimensional portfolio selection problems compared to temporal observation. In such a high-dimensional framework, the asset …