Potentials of machine learning in vacuum electronic devices demonstrated by the design of a magnetron injection gun

Zhang, Liang and Cross, Adrian W. (2021) Potentials of machine learning in vacuum electronic devices demonstrated by the design of a magnetron injection gun. IEEE Transactions on Electron Devices, 68 (6). 3028 - 3033. ISSN 0018-9383

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    Abstract

    Great progress has been made on machine learning and its applications are expanding rapidly nowadays. Through the case study of optimizing a magnetron injection gun for gyrotron devices, the functions of machine learning were investigated by using two supervised learning algorithms, regression trees and artificial neural networks. They showed excellent performance in predicting the outputs, exploring the importance of the input parameters and the relationship with the output parameters. Machine learning can be a useful tool in the development of microwave vacuum electron devices.

    ORCID iDs

    Zhang, Liang ORCID logoORCID: https://orcid.org/0000-0002-6317-0395 and Cross, Adrian W. ORCID logoORCID: https://orcid.org/0000-0001-7672-1283;