摘要
分析了传统BP型神经网络在模拟电路故障诊断中应用所存在的缺点,提出了解决办法。利用遗传算法优化BP网络的结构和具体的参数,可以避免靠经验和试验确定参数的弊端,能够提高神经网络用于模拟电路故障诊断的智能性,改善故障诊断的精度、速度。
The shortages of classic BP Neural Network for fault diagnosis of analo g circuit are put out. A method is put forward to improve the classic BP Neural Network . Genetic algorithm (GA) is use to optimize network structure and specif ic parameters which are usually determined by experience and experiment. The new method improves the automation degree to establish diagnostic model and the acc uracy and efficiency of fault diagnosis.
出处
《自动化与仪表》
2005年第1期4-6,10,共4页
Automation & Instrumentation
基金
国家自然科学基金资助项目(50277010)
高等院校博士学科点专项科研基金资助项目(20020532016)
关键词
神经网络
遗传算法
模拟电路
故障诊断
neural network
genetic algorithm
analog circuit
fault diagnosis
