Journal
APPLIED MATHEMATICAL MODELLING
Volume 40, Issue 11-12, Pages 5745-5758Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2016.01.012
Keywords
Grey forecasting; GMC(1, n); Optimal algorithm; Industrial energy consumption; Economic output
Funding
- National Natural Science Foundation of China [71101132, 71571157]
- Zhejiang Provincial Natural Science Foundation of China [LY15G010005]
- National Statistical Science Foundation of China [2015LY08]
Ask authors/readers for more resources
A grey forecasting model based on convolution integral (GMC(1, n)) is an accurate grey multivariable model, which is derived from the GM(1, n) model by adding a control parameter u. n interpolation coefficients, as unknown parameters, are input into the background values of the n variables so as to improve the adaptability of GMC(1, n) on real data. In addition, a nonlinear optimization model is constructed to obtain the optimal parameters that can minimize the modelling error. The modelling and forecasting results as applied to China's industrial energy consumption show that the optimized grey multivariable model exhibits a higher accuracy than GMC(1, n), SARMA and GM(1, 1). The method proposed for the optimization of the background value can significantly promote the modelling and forecasting precision of GMC(1, n). (C) 2016 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available