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首页> 外文期刊>Network Daily News >Study Findings from Air Force Engineering University Broaden Understanding of Artificial Neural Networks (Real-time Prediction of Characteristic Parameters of Inductively Coupled Plasma Based On Artificial Neural Network)
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Study Findings from Air Force Engineering University Broaden Understanding of Artificial Neural Networks (Real-time Prediction of Characteristic Parameters of Inductively Coupled Plasma Based On Artificial Neural Network)

机译:空军工程大学的研究结果拓宽了对人工神经网络的理解(基于人工神经网络的电感耦合等离子体特征参数的实时预测)

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By a News Reporter-Staff News Editor at Network Daily News – Currentstudy results on Artificial Neural Networks have been published. According to news reporting from Xi’an,People’s Republic of China, by NewsRx journalists, research stated, “Artificial neural networks (ANNs)were implemented to predict the plasma parameter distribution to actively control the plasma absorptionfrequency band. Taking the inductively coupled plasma (ICP) fluid dynamics simulation results as the initialdata, the general regression neural network (GRNN) is introduced to predict the plasma characteristicparameters under any external conditions.”
机译:作者:网络日报新闻的新闻记者-新闻编辑 – 目前关于人工神经网络的研究结果已经发表。根据NewsRx记者中华人民共和国习an的新闻报道,研究表明,“人工神经网络(ANN)被用于预测等离子体参数分布,以主动控制等离子体吸收频带。以电感耦合等离子体(ICP)流体力学仿真结果为初始数据,引入广义回归神经网络(GRNN)预测任意外界条件下的等离子体特性参数。

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