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An Optimized Grey Dynamic Model for Forecasting the Output of High-Tech Industry in China
- Source :
- Mathematical Problems in Engineering, Vol 2014 (2014)
- Publication Year :
- 2014
- Publisher :
- Hindawi Limited, 2014.
-
Abstract
- The grey dynamic model by convolution integral with the first-order derivative of the 1-AGO data andnseries related, abbreviated as GDMC(1,n), performs well in modelling and forecasting of a grey system. To improve the modelling accuracy of GDMC(1,n),ninterpolation coefficients (taken as unknown parameters) are introduced into the background values of thenvariables. The parameters optimization is formulated as a combinatorial optimization problem and is solved collectively using the particle swarm optimization algorithm. The optimized result has been verified by a case study of the economic output of high-tech industry in China. Comparisons of the obtained modelling results from the optimized GDMC(1,n)model with the traditional one demonstrate that the optimal algorithm is a good alternative for parameters optimization of the GDMC(1,n)model. The modelling results can assist the government in developing future policies regarding high-tech industry management.
- Subjects :
- Engineering
Mathematical optimization
Article Subject
Series (mathematics)
business.industry
lcsh:Mathematics
General Mathematics
General Engineering
Combinatorial optimization problem
Particle swarm optimization
lcsh:QA1-939
High tech
lcsh:TA1-2040
lcsh:Engineering (General). Civil engineering (General)
business
Interpolation
Subjects
Details
- ISSN :
- 15635147 and 1024123X
- Volume :
- 2014
- Database :
- OpenAIRE
- Journal :
- Mathematical Problems in Engineering
- Accession number :
- edsair.doi.dedup.....ef43d3bf972a64013608660436044063