摘要
结合了主成分分析和人工神经网络的优点,提出一种基于PCA算法的人工神经网络模型(PCA-ANN模型)来分析高速动车组空心车轴的缺陷。通过算例验证了方法的可行性。
By the advantage of Principal Component Analysis and A rtificial Neural Networks,a kind of A rtificid Neural Networks model （PCA-ANN model） based on PCA algorithm is put forward to analyze the defect of the hollow axle shaft of high-speed train. The case study carried out shows that the algorithm is feasible.
出处
《机械设计与制造》
北大核心
2010年第3期200-201,共2页
Machinery Design & Manufacture
关键词
高速动车组
空心车轴
主成分分析
神经网络
High-speed multiple unit train
Hollow axle shaft
Principal component analysis
Artificial neural networks
