摘要
该文在改进遗传算法和神经网络反向传播算法的基础上,探讨了一种自适应遗传神经算法与结合模型,并将其应用于变压器故障识别。实验数据表明:该算法收敛速度快,能有效地识别故障,对类似电气设备的故障识别有参考价值。
In this paper the adaptive genetic neural algorithm and combining model are discussed based on the improving genetic algorithm and BP algorithm.The paper applies it to transformer's fault recognition.The experiment data show that the algorithm converges quickly and recognizes faults efficiently.It has a reference value for faults recognition of similar electrical equipment.
出处
《计算机工程与应用》
CSCD
北大核心
2003年第35期63-65,共3页
Computer Engineering and Applications
基金
云南省应用基础研究基金资助(编号:2000F0041M)
"控制理论与控制工程"省级重点学科建设项目资助(编号:14039043)
关键词
遗传算法
神经网络
故障识别
变压器
Genetic algorithm,Neural network,Faults recognition,Transformer
