改进蜣螂算法优化LSTM的光伏阵列故障诊断OA北大核心CSTPCD
Improved Dung Beetle Optimizer to Optimize LSTM for Photovoltaic Array Fault Diagnosis
为提高光伏阵列故障诊断精度,提出一种基于变分模态分解VMD(variational mode decomposition)和改进蜣螂算法IDBO(improved dung beetle optimizer)优化长短期记忆LSTM(long short-term memory)网络的光伏阵列故障诊断方法.首先,针对蜣螂算法DBO(dung beetle optimizer)收敛精度低且易陷入局部最优的问题,提出一种融合Levy飞行策略、T分布扰动…查看全部>>
To improve the accuracy of photovoltaic(PV)array fault diagnosis,a PV array fault diagnosis method based on variational mode decomposition(VMD)and improved dung beetle optimizer(IDBO)is proposed to optimize the long short-term memory(LSTM)network. First,in response to the low convergence accuracy of the dung beetle optimizer (DBO)and its tendency to fall into local optima,an IDBO algorithm which integrates the Levy flight strategy,T-distri-bution perturbatio…查看全部>>
李斌;高鹏;郭自强
辽宁工程技术大学电气与控制工程学院,葫芦岛 125105辽宁工程技术大学电气与控制工程学院,葫芦岛 125105辽宁工程技术大学电气与控制工程学院,葫芦岛 125105
动力与电气工程
光伏阵列改进蜣螂算法变分模态分解长短期记忆故障诊断
photovoltaic PV)arrayimproved dung beetle optimizer(IDBO)variational mode decomposition(VMD)long short-term memory(LSTM)fault diagnosis
《电力系统及其自动化学报》 2024 (8)
70-78,9
国家自然科学基金资助项目(51674136、52104160)
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