Projects(60974031,60704011,61174128)supported by the National Natural Science Foundation of China
A self-organizing radial basis function(RBF) neural network(SODM-RBFNN) was presented for predicting the production yields and operating optimization. Gradient descent algorithm was used to optimize the widths of RBF ...
A FCC mechanism model was used to predict the effects of propylene promoter in a 3.0 Mt/a FCCU. The FCC mechanism model was developed based on one set of commercial FCC data without using the promoter, and was modifie...
The National Natural Science Foundation ofChina(No60504033)
A novel nonlinear combination process monitoring method was proposed based on techniques with memo- ry effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis ...
National Nature Science Foundation of China (No60504033)
A novel nonlinear process monitoring and fault detection method based on kernel independent component analysis(ICA) is proposed.The kernel ICA method is a two-phase algorithm:whitened kernel principal component(KPCA) ...
Supported by the National High-Tech Research and Development (863) Program of China (No. 2001AA413320)
The principal component analysis (PCA) algorithm is widely applied in a diverse range of fields for performance assessment, fault detection, and diagnosis. However, in the presence of noise and gross errors, the non...