Applying the K Nearest Neighbor algorithm (KNN) in a microwave filter

this study introduces a novel approach employing the K-nearest neighbor (KNN) algorithm for designing a planar microwave filter. It explores the application of supervised machine learning techniques. in microwave filter design.The inputs to the KNN algorithm primarily consist of geometric variables and frequency, while the outputs are represented by Sparameters. The optimization of the hyperparameter k significantly influences the model’s accuracy. Through experimentation, it is observed that the KNN model achieves predictions with satisfactory to high levels of accuracy.