| 基于改进型BP神经网络的瓦斯传感器的非线性校正 |
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| 引用本文： | 刘刚,刘学仁,嵇英华,罗海梅.基于改进型BP神经网络的瓦斯传感器的非线性校正[J].传感器与微系统,2007,26(1):15-17,20. |
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| 作者姓名： | 刘刚 刘学仁 嵇英华 罗海梅 |
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| 作者单位： | 江西师范大学,物理与通信电子学院,江西,南昌,330022 |
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| 摘 要： | 提出了一种基于改进型BP神经网络的瓦斯传感器的非线性校正方法,利用神经网络良好的非线性映射能力,逼近反非线性函数完成非线行校正。仿真实验结果表明:与传统的分段线性与BP算法相比,改进型的BP神经网络收敛速度快、逼近精度高,准确度由原来分段线性校正的±5.020%提高到现在的±0.130%,且易于动态调校。
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| 关 键 词： | 改进型BP神经网络 瓦斯传感器 非线性校正 |
| 文章编号： | 1000-9787（2007）01-0015-03 |
| 修稿时间： | 2006-07-27 |
Nonlinear correction of methane sensor based on improved BP neural network |
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| LIU Gang,LIU Xue-ren,JI Ying-hua,LUO Hai-mei.Nonlinear correction of methane sensor based on improved BP neural network[J].Transducer and Microsystem Technology,2007,26(1):15-17,20. |
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| Authors: | LIU Gang LIU Xue-ren JI Ying-hua LUO Hai-mei |
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| Abstract: | The nonlinear correction method of methane sensor based on improved BP neural network is introduced to approach inverse nonlinear function by use of nonlinear mapping ability of neural network.The experimental results show that network-learning speed can be sped up markedly and nonlinear precision of the sensor is(±0.130 %) nonlinegr precision of classic paragraph algorithm and BP algorithm is(5.020 %). |
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| Keywords: | improved BP neural network methane sensor and nonlinear correction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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