| 基于径向基函数神经网络的发动机磨损预测分析 |
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| 引用本文： | 刘玉兵,张宗扬,吴国军.基于径向基函数神经网络的发动机磨损预测分析[J].润滑与密封,2009,34(1). |
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| 作者姓名： | 刘玉兵 张宗扬 吴国军 |
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| 作者单位： | 1. 徐州空军学院军交运输指挥系,江苏徐州,221000
2. 徐州空军学院研究生管理大队,江苏徐州,221000 |
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| 摘 要： | 针对BP神经网络算法的不足,利用径向基函数(RBF)神经网络建立设备的磨损预测模型,对光谱分析数据进行实例仿真,并与BP网络模型进行对比研究.仿真结果表明,该模型预测精度高,训练时间短,大大优于BP神经网络模型.
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| 关 键 词： | 径向基函数 神经网络 磨损预测 光谱分析 |
Analysis of Engine Wearing Prediction Based on Radial Basis Function Neural Network |
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| Liu Yubing,Zhang Zongyang,Wu Guojun.Analysis of Engine Wearing Prediction Based on Radial Basis Function Neural Network[J].Lubrication Engineering,2009,34(1). |
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| Authors: | Liu Yubing Zhang Zongyang Wu Guojun |
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| Affiliation: | 1.Department of Military Traffic & Transportation of Xuzhou Air Force College;Xuzhou Jiangsu 221000;China;2.Graduate Administrative Group;Xuzhou Air Force College;China |
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| Abstract: | Due to the defect of BP algorithm,radial basis function(RBF) neural network was applied to establish the model of equipment wearing prediction.The model was used to predict oil spectral analysis data.Compared with BP neural network model,the results indicate that RBF neural network is superior to BP network in the aspects of accuracy and efficiency. |
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| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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