| 金属线胀系数实验误差补偿的新方法——人工神经网络法 |
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| 引用本文： | 郭颖.金属线胀系数实验误差补偿的新方法——人工神经网络法[J].大学物理,2012,31(8):25-28. |
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| 作者姓名： | 郭颖 |
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| 作者单位： | 陕西理工学院 物理与电信工程学院,陕西汉中,723001 |
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| 基金项目： | 陕西理工学院科研基金项目(SLG0916SLG0815)资助 |
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| 摘 要： | 分析光杠杆法测量金属线胀系数实验的误差及误差产生原因,发现温度变化与刻度间隔并非线性变化.对比传统误差分析方法,利用神经网络非线性映射能力,对实验数据进行误差补偿分析,均方根误差达到0.000 01,消除非线性影响,误差降低.
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| 关 键 词： | 金属线胀系数 神经网络 误差补偿 |
Using ANN to error compensation and analysis for experiment of measuring the metal linear expansion coefficient |
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| GUO Ying.Using ANN to error compensation and analysis for experiment of measuring the metal linear expansion coefficient[J].College Physics,2012,31(8):25-28. |
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| Authors: | GUO Ying |
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| Institution: | GUO Ying(School of Physics & Telecommunication Engineering,Shanxi University of Technology,Hanzhong,Shaanxi 723001,China) |
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| Abstract: | This paper analyzes the factors that influence the measure of the metal linear coefficient of expansion in light lever experiment and finds that calibration is nonlinear variation with temperature changing.Artificial neural network(ANN) has more abilities to learning and highly nonlinear reflecting than other traditional method.It is used to error compensation and analysis for experiment,and the simulation result obtained shows that the method is feasible and the calculation is precise. |
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| Keywords: | metal linear expansion coefficient artificial neural network(ANN) error compensation |
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