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The artificial neural network prediction algorithm research of rail-gun current and armature speed based on B-dot probes array

机译:基于B-DOT探针阵列的轨道枪电流和电枢速度的人工神经网络预测算法研究

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In this paper, based on the advantages of artificial neural network, such as good tolerance of data noise, strong ability of nonlinear mapping, multi-dimensional input variables, fast operation, low error, etc., a method of using artificial neural network for data prediction is proposed for the research of rail-gun. The results show that it is feasible to use the Back Propagation Neural Network, the Radial Basis Function Neural Network and the General Regression Neural Network to realize the method of prediction and simulation of the rail-gun current and the armature speed curve through relevant parameters. The General Regression Neural Network has superiority in error performance and time cost of neural network training and simulation. (C) 2018 Published by Elsevier Ltd.
机译:本文基于人工神经网络的优点,如良好的数据噪声容忍,非线性映射能力强,多维输入变量,快速操作,低误差等,一种使用人工神经网络的方法 轨道枪研究提出了数据预测。 结果表明,使用后传播神经网络,径向基函数神经网络和一般回归神经网络是可行的,以实现轨道枪电流的预测和模拟方法,通过相关参数来实现轨道电流的预测和仿真。 一般回归神经网络在神经网络训练和模拟的误差性能和时间成本中具有优越性。 (c)2018由elestvier有限公司出版

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