The Genetic algorithm-Extreme Learning Machine (ga-elm) neuralnetworkalgorithm is proposed to model the relevant characteristics of gaN pseudomorphic high electron mobility transistor (P-HEMT) large signal. This alg...
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The Genetic algorithm-Extreme Learning Machine (ga-elm) neuralnetworkalgorithm is proposed to model the relevant characteristics of gaN pseudomorphic high electron mobility transistor (P-HEMT) large signal. This algorithm solves the over-fitting problem of the Back Propagation (BP) neuralnetworkalgorithm in the prediction data. It has the characteristics of fast calculation speed, so it can greatly save calculation processing time. It can also randomly generate the connection weights of the input layer, the hidden layer and the threshold of the hidden layer neurons, avoiding errors in parameter selection. In order to verify the superiority of the algorithm, the modeling effects of the BP neuralnetworkalgorithm model, the Genetic algorithm-Back Propagation (ga-BP) neuralnetworkalgorithm model and the ga-elm neural network algorithm model are compared in this paper. The results show that the proposed ga-elm neural network algorithm model has the highest accuracy.
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