A Grey NGM ( 1,1 , k ) Self-Memory Coupling Prediction Model for Energy Consumption Prediction
Joint Authors
Guo, Xiaojun
Liu, Sifeng
Wu, Lifeng
Tang, Lingling
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-18
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations.
Although there are several prediction techniques, selection of the most appropriate technique is of vital importance.
As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM ( 1,1 , k ) self-memory coupling prediction model is put forward in order to promote the predictive performance.
It achieves organic integration of the self-memory principle of dynamic system and grey NGM ( 1,1 , k ) model.
The traditional grey model’s weakness as being sensitive to initial value can be overcome by the self-memory principle.
In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique.
The results show the superiority of NGM ( 1,1 , k ) self-memory coupling prediction model when compared with the results from the literature.
Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency.
This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span.
American Psychological Association (APA)
Guo, Xiaojun& Liu, Sifeng& Wu, Lifeng& Tang, Lingling. 2014. A Grey NGM ( 1,1 , k ) Self-Memory Coupling Prediction Model for Energy Consumption Prediction. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1049130
Modern Language Association (MLA)
Guo, Xiaojun…[et al.]. A Grey NGM ( 1,1 , k ) Self-Memory Coupling Prediction Model for Energy Consumption Prediction. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1049130
American Medical Association (AMA)
Guo, Xiaojun& Liu, Sifeng& Wu, Lifeng& Tang, Lingling. A Grey NGM ( 1,1 , k ) Self-Memory Coupling Prediction Model for Energy Consumption Prediction. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1049130
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049130