Combination Forecasting Model Using Grey Verhulst Models Coupling to Regression Analysis

DOI

10.2991/amsm-16.2016.34How to use a DOI?

Keywords

grey verhulst model; fractional order accumulation; significance level; combination forecasting; regression analysis

Abstract

Firstly, grey verhulst model based on fractional order accumulate is deduced. Then, take advantage of differential and difference to find the corresponding relationship between the grey verhulst model of each order and the regression equation. Giving the level of significance , carry out the significance test for the regression equations. Picking up the orders of grey verhulst models corresponding to the first two regression equations which are best-fit for the original time series, then establish the grey verhulst models which have the orders picked up before. Lastly, using these two grey verhulst models to establish the weight arithmetic average combination forecasting model based on grey associate analysis. The practical example indicates that the fitting precision of our model is improved significantly comparing with single forecasting models, logistic model and fractional order accumulate grey verhulst model. It is proved to be an available and practical method for forecasting.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Qing Shu
AU  - Xinping Xiao
PY  - 2016/05
DA  - 2016/05
TI  - Combination Forecasting Model Using Grey Verhulst Models Coupling to Regression Analysis
BT  - Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling
PB  - Atlantis Press
SP  - 148
EP  - 152
SN  - 2352-538X
UR  - https://doi.org/10.2991/amsm-16.2016.34
DO  - 10.2991/amsm-16.2016.34
ID  - Shu2016/05
ER  -