Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)

The Research on Combination Forecast Method of Order Quantity Based on Grey Neural Network

Authors
Yewang Zhou
Corresponding Author
Yewang Zhou
Available Online September 2012.
DOI
10.2991/emeit.2012.13How to use a DOI?
Keywords
combination forecasting, grey prediction, neural network, orders
Abstract

order quantity forecasting in modern enterprise management occupies an important position, order quantity is influenced by many uncertain factors. this paper put forward a prediction method to predict the order quantity based on the combination of grey forecast and artificial neural network, the combination forecasting method can make full use of each single forecasting model, can better improve the prediction accuracy. The method is based on grey prediction model, using the advantages simple algorithm less data and BP neural network to nonlinear system prediction performance advantages, the use of BP nonlinear mapping of neural network combination forecast.

Copyright
© 2012, 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/).

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Volume Title
Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
Series
Advances in Intelligent Systems Research
Publication Date
September 2012
ISBN
978-90-78677-60-4
ISSN
1951-6851
DOI
10.2991/emeit.2012.13How to use a DOI?
Copyright
© 2012, 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/).

Cite this article

TY  - CONF
AU  - Yewang Zhou
PY  - 2012/09
DA  - 2012/09
TI  - The Research on Combination Forecast Method of Order Quantity Based on Grey Neural Network
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 62
EP  - 65
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.13
DO  - 10.2991/emeit.2012.13
ID  - Zhou2012/09
ER  -