KEYWORDS: Neural networks, Education and training, Data modeling, Genetic algorithms, Internet, Evolutionary algorithms, Dielectrics, Data processing, Signal attenuation, Quality control
Impedance control is hard and important for high frequency Printed Circuit Board (PCB). The paper introduces a BP-GA algorithm that applies the optimization on the iteration process of weight parameters during the training process. The results shows that the model has a good performance in impedance prediction of PCB. The RMSE and SSE of this model are 4.083 and 7.003*e3, respectively.
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