基于BA-MKELM的微电网故障识别与定位OACSTPCD
Microgrid Fault Identification and Location Based on BA-MKELM
提出一种基于贝叶斯算法优化多核极限学习机的微电网故障识别和定位方法.针对极限学习机输入参数和隐含层节点数随机选取导致回归能力不足的问题,引入核函数,将多项式与高斯径向基核函数加权组合构成多核极限学习机建立故障识别与定位模型,并采用贝叶斯算法对多核极限学习机相关参数进行优化,进一步提高模型的逼近能力.为了验证所提模型的故障识别与定位性能,选用极限学习机和多核极限学习机分别建立故障诊断模型进行比较分析.实验结果表明,所提方法能够高性能地识别和定位微电…查看全部>>
A microgrid fault identification and location method based on Bayesian algorithm optimizing multi-kernel extreme learning machine is proposed.Aiming at the problem of insufficient regression ability caused by the random selection of input parameters and hidden layer nodes of extreme learning machine,the kernel function is introduced,and the polynomial and the Gaussian radial basis kernel function are combined to form a multi-kernel extreme learning machine t…查看全部>>
吴忠强;卢雪琴
燕山大学工业计算机控制工程河北省重点实验室,河北秦皇岛 066004燕山大学工业计算机控制工程河北省重点实验室,河北秦皇岛 066004
电学计量微电网线路故障识别和定位贝叶斯算法多核极限学习机小波包分解
electrical measurementmicrogrid linefault identification and locationbayesian algorithmmulti-kernel extreme learning machinewavelet packet decomposition
《计量学报》 2024 (2)
253-260,8
河北省自然科学基金(F2020203014)
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