Bibliographic Details
| Title: |
Research on load prediction of back propagation neural networks based on genetic algorithms |
| Authors: |
Yan, Lei, Mu, GuoXing, Wang, Qibing, He, Zhifang, Zhu, Yanfang |
| Source: |
International Journal of High Performance Systems Architecture; 2023, Vol. 11 Issue: 4 p198-205, 8p |
| Abstract: |
To address the problem that back propagation (BP) neural networks are prone to overfitting and falling into local optimality, resulting in low accuracy of electricity load forecasting, this paper proposes a method for electricity load forecasting based on an improved genetic algorithm (GA) and the BP neural network. Through modelling and analysis of load data, better root mean square error (RMSE) and mean absolute percentage error (MAPE) are obtained compared with the traditional BP neural networks, proving the method's superiority. |
| Database: |
Supplemental Index |
