Regression Analysis Based on Wavelet Kernel for Optimization of Chemical Process
Some limitations exist in modeling of chemical process by SVM (support vector machine), such as unsatisfactory modeling accuracy, generalization ability and difficult kernel parameter selection process. To overcome these difficulties, combining wavelet SVM (W-SVM) with Morlet wavelet kernel was described in this article, reproducing kernel space and the wavelet analysis, and the proof to supporting Morlet wavelet kernel function was also given. To show the wavelet kernel function’s better generalization capability and accuracy, the proposed method was applied to establish a soft-sensor model for average molecular weight in polyacrylonitrile (PAN) production process. The results of real data simulation show that this method is effective
Chemical process Wavelet kernel Wavelet support vector machine
ZHENG Rongjian ZHOU Lincheng PAN Feng
Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan Univ Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan Univ
国内会议
厦门
英文
1-4
2012-08-01（万方平台首次上网日期，不代表论文的发表时间）