Paper Title:
An ICA and GM Model for the Innovation Ability Evolution
  Abstract

A three-stage architecture constructed by combining independent component analysis (ICA), gray correlation coefficient analysis (GCCA) and grey model GM(1, N) is proposed for evolution region innovation. In the first stage, ICA is used as feature extraction. In the second stage, GCCA is used as main factors select. In the third stage, GCCA is used to evolution innovation ability. The paper applies the ICA, grey relational analysis and grey non-linear regression analysis to study the factors affecting the ability of independent innovation in Chinese industrial enterprises from the empirical perspective. It is shown that the proposed method achieves is effective and feasible. And it provides a better estimate tool for the innovation activity. It also provides a novel way for the evolution design of the other engineering.

  Info
Periodical
Advanced Materials Research (Volumes 204-210)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
1305-1309
DOI
10.4028/www.scientific.net/AMR.204-210.1305
Citation
X. L. Lv, "An ICA and GM Model for the Innovation Ability Evolution", Advanced Materials Research, Vols. 204-210, pp. 1305-1309, 2011
Online since
February 2011
Authors
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Yi Liu, Hong Ying Deng, Zeng Liang Gao, Ping Li
Abstract:A novel two-level integrated soft sensor modeling method using kernel independent component analysis (KICA) and support vector regression...
560
Authors: Hua Zheng, Li Xie, Li Zi Zhang
Abstract:There is a general consensus that the movement of electricity price is crucial for electricity market. As a practical tool to estimate the...
1289
Authors: Zhi Yang Jia, Pu Wang, Xue Jin Gao
Chapter 6: Navigation Systems, Monitoring and Detection Technology
Abstract:In the process monitoring and fault diagnosis of batch processes, traditional principal component analysis (PCA) and least-squares (PLS), are...
1783