Design optimization of many electromagnetic and multiphysics problems have multiscale issues that require a fast, efficient, and accurate surrogate‐based model to be used. Recently, in microwave engineering field, artificial intelligence–based models are being used for modeling of complex microwave stages. In all the studies, the main aim is to form models inner structure parameters, by using the given data to predict the linear/nonlinear relationships between given inputs and outputs. Herein, a surrogate‐based model of a nonuniform microstrip transmission line (NTL) with a typical application of design optimization of a band‐pass filter for ISM band application using deep learning (DL) and meta‐heuristic optimization has been presented. In order to have a computationally efficient and accurate optimization process, firstly a 3D EM unit element model of NTL has been designed. The training and test data sets are created based on different sampling methods. A DL regression model modified multilayer perceptron M2LP have been used for prediction of scattering parameters (S) of the NTL, with respect to the variation of geometrical design parameters. The proposed S‐parameters will then be used to calculate the equivalent S‐parameters of the cascading NTL to be used to calculate the NTL‐based microstrip band‐pass filter S‐parameter response. The optimal design parameters of each line used in the filter design have been determined using a fast and powerful optimization algorithm differential evolutionary algorithm.
Herein, by using 3D printing technology and data‐driven surrogate model‐assisted optimization method, design of a ceramic material‐based nonuniform nonplanar microstrip filter is taken into the consideration in a computationally efficient and low‐cost manner. For this aim, 3D EM model of the proposed design had been used for generating training and validation data sets. Then commonly used state‐of‐the‐art regression algorithms had been used for creating accurate and fast surrogate models to create a mapping between inputs of the model and outputs of the unit element design. After that, Grey Wolf Optimization algorithm had been used for design optimization of a bandpass filter. Then, via the use of 3D printer, the optimally designed filter had been prototyped and its performance characteristics are measured. As a result, by using 3D printer technology, ceramic material, and the proposed method, design optimization of nonuniform nonplanar microstrip filter can be achieved in a computationally efficient way.
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