Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)

Electricity consumption forecasting method based on MPSO-BP neural network model

Authors
Youshan Zhang, Liangdong Guo, Qi Li, Junhui Li
Corresponding Author
Youshan Zhang
Available Online December 2016.
DOI
10.2991/iceeecs-16.2016.133How to use a DOI?
Keywords
MPSO-BP algorithm; Electricity consumption; Neural network; Forecasting model
Abstract

This paper deals with the problem of the electricity consumption forecasting method. A MPSO-BP(modified particle swarm optimization-back propagation) neural network model is constructed based on the history data of a mineral company of Anshan in China. The simulation showed that the convergence of the algorithm and forecasting accuracy using the obtained model are better than those of other traditional ones, such as BP,PSO, fuzzy neural network and so on. Then we predict the electricity consumption of each month in 2017 based on the MPSO-BP neural network model.

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/).

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Volume Title
Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-265-7
ISSN
2352-538X
DOI
10.2991/iceeecs-16.2016.133How to use a DOI?
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/).

Cite this article

TY  - CONF
AU  - Youshan Zhang
AU  - Liangdong Guo
AU  - Qi Li
AU  - Junhui Li
PY  - 2016/12
DA  - 2016/12
TI  - Electricity consumption forecasting method based on MPSO-BP neural network model
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 674
EP  - 678
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.133
DO  - 10.2991/iceeecs-16.2016.133
ID  - Zhang2016/12
ER  -