U-slot Loaded Flared-U Fractal Antenna Analysis using ANN

The U-slot loaded fractal antenna is studied using the HFSS and Machine Learning (ML) algorithms. The HFSS tool is being used for designing and analyzing fractal antennas. To generate the training data, the HFSS tool is used. The next step is to apply the training data to Machine Learning Artificial Neural Network(ANN). A U-slot-loaded microstrip antenna is under consideration for Wi-Fi applications. On the micro strip patch antenna, the patch is flared on the four sides with the fractal curves. Then a U-slot is inserted. For parametric analysis, the fractal depth and the U-curve’s length and width are modified. The main parameter used is resonant frequency. This frequency varies by varying the parameters considered. This can be achieved by using parametric analysis. After performing the parametric analysis, the training dataset is generated. Fractal depth, U-slot length and U-slot width are considered as the parameters to generate the dataset. The training data set is then evaluated using the machine learning algorithm ANN. ANN’s require large amounts of data training data to be effective. This could result in poor performance and inaccurate results. The proposed approach reduces the computational time required for antenna analysis and design, making it suitable for practical applications.