A step toward next-generation advancements in the internet of things technologies
The Internet of Things (IoT) devices generate a large amount of data over networks;
therefore, the efficiency, complexity, interfaces, dynamics, robustness, and interaction need …
therefore, the efficiency, complexity, interfaces, dynamics, robustness, and interaction need …
Intelligent multimedia content delivery in 5G/6G networks: a reinforcement learning approach
Multimedia content in 5G/6G networks makes safe, confidential, and efficient content
delivery difficult. Intelligent systems that adapt to the ever‐changing network environment …
delivery difficult. Intelligent systems that adapt to the ever‐changing network environment …
Transfer learning for financial data predictions: a systematic review
V Lanzetta - arXiv preprint arXiv:2409.17183, 2024 - arxiv.org
Literature highlighted that financial time series data pose significant challenges for accurate
stock price prediction, because these data are characterized by noise and susceptibility to …
stock price prediction, because these data are characterized by noise and susceptibility to …
Optimization of Cryptocurrency Algorithmic Trading Strategies Using the Decomposition Approach
A cryptocurrency is a non-centralized form of money that facilitates financial transactions
using cryptographic processes. It can be thought of as a virtual currency or a payment …
using cryptographic processes. It can be thought of as a virtual currency or a payment …
The Evolution of Reinforcement Learning in Quantitative Finance
Reinforcement Learning (RL) has experienced significant advancement over the past
decade, prompting a growing interest in applications within finance. This survey critically …
decade, prompting a growing interest in applications within finance. This survey critically …
Outperforming Cryptocurrency Price Prediction Using Deep Reinforcement Learning Approach
PVRS Rao, B Natarajan… - 2023 International …, 2023 - ieeexplore.ieee.org
Cryptocurrency price prediction is a complex and dynamic task. Cryptocurrencies are highly
volatile digital assets impacted by a wide range of variables, including investor mood …
volatile digital assets impacted by a wide range of variables, including investor mood …
Reinforcement Learning Techniques for Stock Trading: A Survey of Current Research.
Reinforcement learning (RL) has emerged as a promising approach for developing
intelligent trading systems in the stock market. The intention of this survey article is to …
intelligent trading systems in the stock market. The intention of this survey article is to …
FP-WDDQN: An improved deep reinforcement learning algorithm for adaptive traffic signal control
X Zhang, X Xu - 2023 IEEE International Conference on Data …, 2023 - ieeexplore.ieee.org
Current adaptive traffic signal control methods based on centralized deep reinforcement
learning are not applicable in large-scale adaptive traffic control environment. The scalability …
learning are not applicable in large-scale adaptive traffic control environment. The scalability …
Deep Reinforcement Learning in Financial Markets Context: Review and Open Challenges
Y Boutyour, A Idrissi - Modern Artificial Intelligence and Data Science …, 2023 - Springer
The advancement of reinforcement learning techniques has increased their application
across many industries, including the financial markets. An overview of reinforcement …
across many industries, including the financial markets. An overview of reinforcement …
Bitcoin Optimized Signal Allocation Strategies using Decomposition.
SM Omran, WH El-Behaidy… - International Journal of …, 2023 - search.ebscohost.com
Bitcoin is the first and most famous cryptocurrency. It is a virtual currency that is operated in a
decentralized form using cryptographic strategies called blockchains. Although it has …
decentralized form using cryptographic strategies called blockchains. Although it has …