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
- 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.
- 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 - 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 - Proceedings of the 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 - 10.2991/icemse-16.2016.90 ID - Zhao2016/12 ER -