Application of Improved RBFNN in Comprehensive Evaluation for Maintenance Quality
According to the characteristics of evaluation of maintenance quality, in this paper partial least squares (PLS) is adopted to improve the common least squares (LS), and the maintenance quality evaluation model based on FCM-PLSRBFNN is set up, and the learning and training algorithm is provided for FCM-PLS-RBFNN, and the improving effect of the model and its validity and precision in maintenance quality evaluation is tested by the living example of certain equipment maintenance quality comprehensive evaluation. The result shows that the FCM-PLS-RBFNN is faster than FCM-LS-RBFNN in learning, and its approaching ability and popularize performance are improved obviously. It is workable and effective to apply the FCM-PLS-RBFNN in modeling and evaluating for maintenance quality. It provides new ideas for researching on the more external and better popularizes maintenance quality evaluation method.
RBF neural networks maintenance quality comprehensive evaluation fuzzy c-means clustering) partial least squares
Shengfeng WANG Hongwei WANG Mingfang NI Deqi KOU Xun TONG
Department of Technical Support Engineering Academy of Armored Forces Engineering Beijing, China
国际会议
西安
英文
825-828
2011-06-17（万方平台首次上网日期，不代表论文的发表时间）