CIESC Journal ›› 2011, Vol. 62 ›› Issue (8): 2367-2371.
Previous Articles Next Articles
LI Dazi,QIAN Li,WANG Shuhong,JIN Qibing
Online:
Published:
李大字,钱丽,王淑红,靳其兵
Abstract:
A modeling method by radial basis function(RBF)network based on enhanced global K’-means algorithm(EGK’M)was presented.An EGK’M algorithm was proposed to determine the hidden layer structure of RBF network,including the number of hidden layer nodes,the position of each center and the width of basis function.KPCA algorithm was used to extract non-linear feature information and to achieve secondary selection of auxiliary variable.The obtained model was compared with the model based on principle components analysis with EGK’M-RBF and the model based on KPCA with RBF network based on K’-means algorithm.Experiment results demonstrate that the model proposed in this paper gives better predictive ability,smaller absolute error and mean square error.
Key words: FONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA">改进的全局FONT-SIZE: 9pt, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA, mso-fareast-font-family: 宋体, mso-hansi-font-family: 宋体" lang=EN-US>KFONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA">’FONT-SIZE: 9pt, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA, mso-fareast-font-family: 宋体, mso-hansi-font-family: 宋体" lang=EN-US>-meansFONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA">算法FONT-SIZE: 9pt, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA, mso-fareast-font-family: 宋体, mso-hansi-font-family: 宋体" lang=EN-US>;FONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-fo
摘要:
提出一种基于增强的全局K’-means算法(EGK’M)-RBF网络的建模方法,该方法采用作者提出的 EGK’M来确定RBF网络隐含层的结构,包括隐含层中心个数、中心位置以及隐含层扩展常数,采用KPCA提取非线性特征信息,实现辅助变量的二次选择。并与基于PCA和EGK’M-RBF网络模型、基于 关键词: FONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA">改进的全局FONT-SIZE: 9pt, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA, mso-fareast-font-family: 宋体, mso-hansi-font-family: 宋体" lang=EN-US>KFONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA">’FONT-SIZE: 9pt, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA, mso-fareast-font-family: 宋体, mso-hansi-font-family: 宋体" lang=EN-US>-meansFONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA">算法FONT-SIZE: 9pt, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA, mso-fareast-font-family: 宋体, mso-hansi-font-family: 宋体" lang=EN-US>;FONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-fo
关键词: FONT-SIZE: 9pt, mso-ascii-font-family: Calibri, mso-ascii-theme-font: minor-latin, mso-fareast-theme-font: minor-fareast, mso-bidi-font-family: 宋体, mso-ansi-language: EN-US, mso-fareast-language: ZH-CN, mso-bidi-language: AR-SA">改进的全局
CLC Number:
TP 273
LI Dazi, QIAN Li, WANG Shuhong, JIN Qibing. Estimation of Mooney viscosity of polybutadiene rubber based on EGK’M-RBF network[J]. CIESC Journal, 2011, 62(8): 2367-2371.
李大字, 钱丽, 王淑红, 靳其兵. 基于EGK’M-RBF网络的顺丁橡胶门尼黏度预测 [J]. 化工学报, 2011, 62(8): 2367-2371.
0 / / Recommend
Add to citation manager EndNote|Ris|BibTeX
URL: https://hgxb.cip.com.cn/EN/
https://hgxb.cip.com.cn/EN/Y2011/V62/I8/2367