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Automated Model Generation (AMG) algorithms are an important technique for creating Artificial Neural Network (ANN) models in microwave design automation. AMG integrates all the subtasks in ANN development into a unified automated algorithm. The assessments of the ANN training phenomena related to under-learning, over-learning and good-learning are automated and the quantitative links between the accuracy of the ANN model, the amount/distribution of training/testing data, and the size of the neural network are established. In this way, the AMG algorithm automatically creates an ANN model with user-desired accuracy, significantly reducing the human time required for modeling. This paper introduces the state of the art in AMG algorithms and its applications in microwave modeling.
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Na et al. (2025) studied this question.
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