Proceedings of the 2016 International Conference on Education, Management Science and Economics

Research on BP Neural Network Algorithm Based on Genetic Algorithm Optimization in Short-Term Power Generation Forecasting

Authors
Jianna Zhao, Xiaobo He
Corresponding Author
Jianna Zhao
Available Online December 2016.
DOI
https://doi.org/10.2991/icemse-16.2016.90How to use a DOI?
Keywords
Genetic algorithm, forecasting, BP neural network
Abstract
In order to overcome the shortcomings of traditional BP neural network, and realize the fast and accurate prediction, this paper will construct a new prediction method by combining genetic algorithm and neural network. The method significantly improves the optimization ability of the model, which can effectively overcome the slow learning speed of neural network, and overcome the blindness of the initial weights of the neural network, so as to effectively improve the accuracy of prediction. The examples show that this method can effectively improve the prediction accuracy.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Conference on Education, Management Science and Economics
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
December 2016
ISBN
978-94-6252-275-6
ISSN
2352-5398
DOI
https://doi.org/10.2991/icemse-16.2016.90How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jianna Zhao
AU  - Xiaobo He
PY  - 2016/12
DA  - 2016/12
TI  - Research on BP Neural Network Algorithm Based on Genetic Algorithm Optimization in Short-Term Power Generation Forecasting
BT  - 2016 International Conference on Education, Management Science and Economics
PB  - Atlantis Press
SP  - 359
EP  - 362
SN  - 2352-5398
UR  - https://doi.org/10.2991/icemse-16.2016.90
DO  - https://doi.org/10.2991/icemse-16.2016.90
ID  - Zhao2016/12
ER  -