CAJ | 학술논문

极限学习机具有学习速度快、精度高的优点。为了进一步提高泛化能力，将差分进化算法的全局寻优和算法简单的特点引入到极限学习机的参数优化中，建立了基于差分进化算法优化极限学习机的模型，使两种算法的优点有机结合，应用于模拟电路故障诊断中。首先利用主元分析对电路采样信号进行处理，提取故障特征；其次利用差分进化算法的全局寻优能力优化极限学习机网络的权值和阈值，具有很好的泛化能力。此方法应用于电路仿真实例中，能在较短的时间内获得满意的结果。
겁한학습궤구유학습속도쾌、정도고적우점。위료진일보제고범화능력，장차분진화산법적전국심우화산법간단적특점인입도겁한학습궤적삼수우화중，건립료기우차분진화산법우화겁한학습궤적모형，사량충산법적우점유궤결합，응용우모의전로고장진단중。수선이용주원분석대전로채양신호진행처리，제취고장특정；기차이용차분진화산법적전국심우능력우화겁한학습궤망락적권치화역치，구유흔호적범화능력。차방법응용우전로방진실례중，능재교단적시간내획득만의적결과。
Extreme learning machine has quick learning speed and high accuracy. To improve the generalization perfor-mance, differential evolution algorithm, which has the features of global convergence and easy computation, is introduced in the parameter optimization of extreme learning machine. A parameter optimization model based differential evolution algorithm is established in order to combine the advantages of the algorithms, applied in analog circuit fault diagnosis. Firstly, the output voltage signals from the test nodes of all analog circuit are obtained and the fault feature vectors are extracted from principal component analysis. Then, using differential evolution algorithm global optimization ability encodes the connection weights and thresholds to get the optimal structure, achieving good generalization performance and robust-ness. This approach applied in diagnosis is more effective and can get satisfied results in a short time.