摘要
BP算法的研制成功使神经网络达到了实用化程度 .然而在实际工程中神经网络还没有起到其应起的作用 ,主要原因不在神经网络本身而在各领域的使用者未能把重点放在输入数据的前处理上 .根据航天器故障诊断的特点 ,提出了根据数据特点来构造前处理函数的改进的升半柯西数据归一化方法 .通过比较证明 ,采用这一归一化方法可大大提高神经网络故障诊断系统的准确性 .
Discusses the BP algorithm proposed for neural networks, which made the neural networks practical for use although the neural networks has not been applied properly because the user failed to stress the pre treatment of input data neural networks and proposes an improved Cauchy method of normalization of input data in the light of the characters of spacecraft, and methods of constructing normalization functions and concludes from comparison of these methods that normalization is the key reason having effect on the correctness of faults diagnosis in spacecraft.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
2001年第1期65-67,72,共4页
Journal of Harbin Institute of Technology
关键词
神经网络
故障诊断
数据归一化
航天器
电源系统
artificial intelligence neural networks
fault diagnosis
data normalization
spacecraft.
