| 基于粗糙集神经网络的故障诊断 |
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| 引用本文： | 闫君,申东日,陈义俊,陈凤.基于粗糙集神经网络的故障诊断[J].哈尔滨商业大学学报(自然科学版),2007,23(4):488-491. |
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| 作者姓名： | 闫君 申东日 陈义俊 陈凤 |
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| 作者单位： | 辽宁石油化工大学,信息与控制工程学院,辽宁,抚顺,113001 |
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| 摘 要： | 在神经网络故障诊断模型的基础上,引入粗糙集理论,给出连续属性值的离散化方法.并应用粗糙集对故障诊断决策表进行属性约简,剔除其中不必要的属性.仿真结果表明,该方法可以有效地减少输入层个数,简化神经网络结构,减少网络的训练时间,在故障诊断中有良好的应用前景.
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| 关 键 词： | 故障诊断 神经网络 粗糙集 约简 离散化 |
| 文章编号： | 1672-0946（2007）04-0488-04 |
| 收稿时间： | 2006-07-11 |
| 修稿时间： | 2006-07-11 |
Fault diagnosis based on rough set and neural network |
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| YAN Jun,SHEN Dong-ri,CHEN Yi-jun,CHEN Feng.Fault diagnosis based on rough set and neural network[J].Journal of Harbin University of Commerce :Natural Sciences Edition,2007,23(4):488-491. |
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| Authors: | YAN Jun SHEN Dong-ri CHEN Yi-jun CHEN Feng |
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| Abstract: | On the basis of neural network fault diagnosis model,this paper introducs rough sets theory and disctete method of continous attribute value.And rough sets theory is used to eliminate unnessary attributes from the decision table.The result of emluator indicats that this method can reduce the needed training samples and simply the neural network structure and shortened the training time of the network.It is estimated that the optimized strategy may be further applied in fault diagnoses. |
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| Keywords: | fault diagosis neural network rough sets reduction discretization |
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