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@article{166887,
        author = {Dr.S.Komalavalli and M S Umasankar and V LAKSHMANAN},
        title = {Designing and Evaluating THz Antenna using Machine Learning for 6G Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {2},
        pages = {2189-2197},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=166887},
        abstract = {For improving technology there is a need for High speed internet, sixth generation Technology is becoming more important. To achieve the required performance and capabilities, the development of an ideal antenna is essential. However, the conventional method of simulating electromagnetic fields for antenna design are laborious and computationally demanding, lengthy simulation times and need powerful computers. Terahertz (THz) antenna design and Machine Learning (ML) technology can be applied to address these constrains. The goal of this work is to design an antenna which operate in THz Band and it is a crucial 6G Band for the upcoming infrastructure revolution. Additionally machine learning models such as decision tree, random forest and Mean Square Error (MSE) is used to predict and optimize the return loss of the antenna. The results demonstrate the accuracy of each models with Random forest exhibiting the highest accuracy of 82% in return loss prediction. New development of effective and optimized 6G antenna for High speed communication are provided by machine learning.},
        keywords = {Antenna, ML, MSE, THz.},
        month = {July},
        }