This review paper provides an overview of the latest developments in artificial intelligence
(AI)-based antenna design and optimization for wireless communications. Machine learning …

Deep learning (DL) plays a vital role in the design of electromagnetic (EM) structures.
However, in current research, a single neural network typically supports only one structure …

This article introduces a machine learning (ML) framework for the design of space–time-
coding digital metasurface elements (STCDMEs), commonly used in reconfigurable …

Machine learning (ML) has demonstrated significant potential in accelerating the design of
microwave components owing to its great ability to approximate the projection between …

This chapter gives an overview of how machine learning algorithms can be employed in
designing and optimizing antennas. Antenna design and optimization is a major factor that …

Deep-learning-assisted antenna design methods such as surrogate models have gained
significant popularity in recent years due to their potential to greatly increase design …

In this article, deep reinforcement learning (DRL) is utilized to explore high-performance
folded-waveguide (FWG) slow-wave structures (SWSs) for broadband application in …

In this paper, an imitation-interaction learning (Imit-IR) method is proposed for multi-zone
ventilation systems, to enhance the ventilation control performance and optimizes system …

In the context of forthcoming sixth-generation (6G) wireless communication, the sub-
terahertz and terahertz frequency spectrum are anticipated. At such high frequencies …

In recent years, deep learning has emerged as a powerful data-driven approach to transform
the way we discover, design, and utilize metasurfaces (MSs). In this paper, we propose an …