论文信息 - Intellectual recognition of reliability analysis model based on neural network integration

Intellectual recognition of reliability analysis model based on neural network integration

Intellectual recognition method for the reliability distribution models based on neural network integration has been studied. Normal distribution, Weibull distribution and logarithmic normal distribution are tested and analyzed. The simulation test results tell us that the intellectual recognition system has high confidence degree and high recognition rate, and is easy to be implemented in engineering.

Li Li | Zhi Gao

[1] Eric Bauer,et al. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants , 1999, Machine Learning.

[2] Samuel Kaski,et al. Bibliography of Self-Organizing Map (SOM) Papers: 1981-1997 , 1998 .

[3] Anders Krogh,et al. Learning with ensembles: How overfitting can be useful , 1995, NIPS.

[4] Wei Tang,et al. Ensembling neural networks: Many could be better than all , 2002, Artif. Intell..

[5] Sungzoon Cho,et al. Observational Learning Algorithm for an Ensemble of Neural Networks , 2002, Pattern Analysis & Applications.

[6] Martin Anthony,et al. Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants , 1994 .