Title :
The improvements of forecast model for regional independent innovation output ability
Author_Institution :
Manage. Sch., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
To study the independent innovation capability of Chinese provinces and those development situation, this paper establishes a set of evaluation and forecasting model. In order to evaluate Independent Innovation output Capacity of the regions, the independent innovation capacity factor are found by factor analysis. And then focus on science and technology system characteristics, growth rate data and time series data are added to an improved artificial neural network prediction model. Empirical results show that not only the generalization capability of the prediction model is enhanced but also the prediction accuracy is improved. So the accurate predict of the development of regional independent innovation ability is achieved. Therefore the article has a double value of theory and practice.
Keywords :
forecasting theory; generalisation (artificial intelligence); innovation management; neural nets; prediction theory; regional planning; time series; Chinese provinces; artificial neural network; forecast model; generalization capability; prediction model; regional independent innovation output ability; science and technology system characteristics; time series; Artificial neural networks; Data models; Economics; Patents; Predictive models; Technological innovation; Time series analysis; evaluation; improved forecast; independent innovation output ability;
Conference_Titel :
Business Management and Electronic Information (BMEI), 2011 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-61284-108-3
DOI :
10.1109/ICBMEI.2011.5920513