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Lately, there has been a remarkable increase in fascination within the field of AI-assisted communications, especially regarding its ability to offer solutions for mathematical challenges within wireless communications through the utilization of Machine learning (ML) and Deep Learning (DL) algorithms. Machine learning grants greater adaptability in design and augments the possibilities for integration and fabrication in antenna technology, thereby aiding in the fulfillment of the increasingly stringent requirements of contemporary antennas. This paper offers a comprehensive review of the application of ML algorithms in the designing of antenna and optimizing the performance, with potentially profound ramifications for the advancement of antennas in diverse applications in the future. The comparison of various ML methods in the design of antennas is illustrated.
Lalhriatpuii et al. (Sat,) studied this question.