A Prediction of the China´s Scientific and Technological Input and Output by Artificial Neural Network Model

Author

Yingnan, Zhang

Author_Institution

Sch. of Econ., Sichuan Univ., Chengdu, China

fYear

2010

fDate

24-26 March 2010

Firstpage

357

Lastpage

362

Abstract

Based on analyzing evolution of production models related to scientific and technical factors, as well as against not well describing quantitative relations between scientific and technical input and output of the models, the present paper has established a model simulating scientific and technological input and output with the back-propagation algorithm of artificial neural networks model, and predicted 1.5% growth rate of China´s GDP output contributed by science and technology in 2007-2016,from 1527.6 billion to 1759 billion in 4% growth rate of scientific and technological labor input and 14% -capital input as the input levels in the years 2007- 2016.

Keywords

backpropagation; economic indicators; neural nets; China GDP output; artificial neural network model; back-propagation algorithm; model simulating scientific output; model simulating technological output; production models evolution; scientific input; technical input; technological labor input; Analytical models; Artificial neural networks; Computer simulation; Economic indicators; Equations; Paper technology; Predictive models; Production; Productivity; Research and development;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Modelling and Simulation (UKSim), 2010 12th International Conference on

Conference_Location

Cambridge

Print_ISBN

978-1-4244-6614-6

Type

conf

DOI

10.1109/UKSIM.2010.73

Filename

5480462