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

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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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  -