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您的检索式：作者名="Saeid NIKBAKHT"
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| 1 | Optimizing the neural network hyperparameters utilizing genetic algorithm显示文摘Neural networks(NNs),as one of the most robust and efficient machine learning methods,have been commonly used in solving several problems.However,choosing proper hyperparameters(e.g.the numbers of layers and neurons in each layer)has a significant influence on the accuracy of these methods.Therefore,a considerable number of studies have been carried out to optimize the NN hyperpaxameters.In this study,the genetic algorithm is applied to NN to find the optimal hyperpaxameters.Thus,the deep energy method,which contains a deep neural network,is applied first on a Timoshenko beam and a plate with a hole.Subsequently,the numbers of hidden layers,integration points,and neurons in each layer are optimized to reach the highest accuracy to predict the stress distribution through these structures.Thus,applying the proper optimization method on NN leads to significant increase in the NN prediction accuracy after conducting the optimization in various examples. | Saeid NIKBAKHT Cosmin ANITESCU Timon RABCZUK | 2021 | Journal of Zhejiang University-Science A(Applied Physics & Engineering)2021，22，6： | 5 |
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