학술논문

Application of grey prediction theory to forecast technology input within the Chinese High-Tech Industries
Document Type
Conference
Author
Source
2011 3rd International Conference on Advanced Computer Control Advanced Computer Control (ICACC), 2011 3rd International Conference on. :88-92 Jan, 2011
Subject
Computing and Processing
Robotics and Control Systems
Predictive models
Accuracy
grey theory
technology input
gm(1,1) method
regression model
Chinese high-tech industries
Language
Abstract
Based on the statistical data, over the period from 2004 to 2008 released by China Statistical Yearbook on High Technology Industry (2009), this paper aims to predict the amount of technology input, mainly including scientists and engineers, funds for science and technology activities within the Chinese high-tech industries by the usage of GM (1,1) model with the five items. The result of this empirical study is that the GM (1,1) model established in this paper can fit the amount of technology input which consists of scientists and engineers, funds for science and technology activities within the Chinese high-tech industries. The accuracy of the prediction result from the established GM (1,1) model is above 90% and is higher than that from the established regression model in this paper, and corresponds with a distinction, which the grey prediction theory can meet expectations with small samples or data. Research results show that this established GM(1,1) model could provide valuable information for policy makers in their efforts to make appropriate technological policies within the Chinese high-tech industries.