Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

3rd Annual International Workshop on Materials Science and Engineering

Wen, Lei^1 ; Yu, Jiake^1 ; Zhao, Xin^2

Department of Economics and Management, North China Electric Power University, Baoding, Hebei

071003, China^1

Economic and Technology Research Institute of Xinjiang Electric Power Company, Wulumiqi, Xinjiang, 840000, China^2

关键词: BP model;    BP neural networks;    Electric power engineering;    GA-BP algorithms;    Hybrid predictions;    PCA algorithms;    Predicting models;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/250/1/012011/pdf
DOI  :  10.1088/1757-899X/250/1/012011

来源: IOP

【 摘 要 】

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.