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 …
Machine learning methods in smart lighting toward achieving user comfort: a survey
Smart lighting has become a universal smart product solution, with global revenues of up to
US 5.9 billion by 2021. Six main factors drive the technology: light-emitting diode (LED) …
US 5.9 billion by 2021. Six main factors drive the technology: light-emitting diode (LED) …
Machine learning in absorption-based post-combustion carbon capture systems: A state-of-the-art review
The enormous consumption of fossil fuels from various human activities leads to a significant
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …
Fault detection and isolation of control moment gyros for satellite attitude control subsystem
Control moment gyros, as one of the most commonly used actuators onboard satellites, are
prone to faults and failures. The ability to detect faults, isolate their location, and identify their …
prone to faults and failures. The ability to detect faults, isolate their location, and identify their …
Automatic web content personalization through reinforcement learning
This paper deals with the automatic adaptation of Web contents. It is recognized that quite
often users need some personalized adaptations to access Web contents. This is more …
often users need some personalized adaptations to access Web contents. This is more …
An efficient initialization approach of Q-learning for mobile robots
Y Song, Y Li, C Li, G Zhang - … Journal of Control, Automation and Systems, 2012 - Springer
This article demonstrates that Q-learning can be accelerated by appropriately specifying
initial Q-values using dynamic wave expansion neural network. In our method, the neural …
initial Q-values using dynamic wave expansion neural network. In our method, the neural …
Designing of on line intrusion detection system using rough set theory and Q-learning algorithm
Development of an efficient real time intrusion detection system (IDS) has been proposed in
the paper by integrating Q-learning algorithm and rough set theory (RST). The objective of …
the paper by integrating Q-learning algorithm and rough set theory (RST). The objective of …
Smart dairy farming overview: innovation, algorithms and challenges
The recent increase in world population has correspondingly triggered an increase in dairy
demand subsequently giving rise to the global hunger problem. The global hunger problem …
demand subsequently giving rise to the global hunger problem. The global hunger problem …
Reinforcement learning: a friendly introduction
Reinforcement Learning (RL) is a branch of machine learning (ML) that is used to train
artificial intelligence (AI) systems and find the optimal solution for problems. This tutorial …
artificial intelligence (AI) systems and find the optimal solution for problems. This tutorial …
Joint Power Allocation and User Fairness Optimization for Reinforcement Learning Over mmWave-NOMA Heterogeneous Networks
In this paper, the problem of joint power allocation and user fairness is investigated for an
mmWave heterogeneous network (HetNet) including hybrid non-orthogonal multiple access …
mmWave heterogeneous network (HetNet) including hybrid non-orthogonal multiple access …