Abstract
According to the research on the structure of background value in the GM(1,1) model, the background value’s structure method of GM(1,1) model, a exact formula about the background value of X (1) (t) in the region [k, k + 1],which is used when establishing GM(1,1), is established by integrating X (1) (t) from k to k + 1. The modeling precision and prediction precision of the ameliorating background value can be advanced.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Liu, S., Guo, T., Dang, Y.: Grey System Theory and Its Application. Science Press, Beijing (1999)
Tan, G.: The Structure Method and Application of Background Value in Grey System GM (1, 1) Model(I). Systems & Engineering-Theory, 98–103 (2004)
Chen, T.: A New Development of Grey Forecasting Model. Systems Engineering, 50–52 (1990)
Fu, L.: Systematic Theory and Application. Scientific Technical Document Publishing House (1992)
Shi, G., Yao, G.: Application of Grey System Theory in Fault Tree Diagnosis Decision. Systems Engineering theory & Practice 144, 120–123 (2001)
Gong, W., Shi, G.: Application of Gray Correlation Analysis in the Fe-spectrum Analysis Technique. Journal of Jiangsu University of Science and Technology (Natural Science), 59–61 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, C., Ye, J., Zheng, F. (2012). Ameliorating GM (1, 1) Model Based on the Structure of the Area under Parabola. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_36
Download citation
DOI: https://doi.org/10.1007/978-3-642-24553-4_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24552-7
Online ISBN: 978-3-642-24553-4
eBook Packages: Computer ScienceComputer Science (R0)