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Based on rough sets and L1 regularization of the fault diagnosis of linear regression model

机译:基于线性回归模型故障诊断的粗糙集和L1正则化

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The purpose of this article is to network fault diagnosis, a higher knowledge more than soft, using least squares estimation precision, low efficiency, thus put forward the new type of rough sets and L1 regularization method network fault diagnosis model. Thus obtained in the network fault diagnosis for large amounts of data regression fitting its computational efficiency, diagnostic accuracy, stability has improved significantly.
机译:本文的目的是网络故障诊断,更高的知识多于软,使用最小二乘估计精度,低效率,从而提出了新型的粗糙集和L1正则化方法网络故障诊断模型。由此获得的网络故障诊断大量数据回归拟合其计算效率,诊断准确性,稳定性显着提高。

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