Title :
Electric power consumption forecast of life energy sources based on fuzzy neural network
Author :
Xiufeng, Shao ; Jian, Zhang
Author_Institution :
Dept. of Soft & Inf. Manage., BeiJing City Univ., Beijing, China
Abstract :
A fuzzy neural network(FNN) with five layers is proposed in this article. Aim at the structure optimization of network, a new node selection method and corresponding back propagation learning algorithm are presented. We use real history data to train the network model at the same time and to forecast the result after the train finished. Test results illustrate its good practicability to power consumption forecast of life energy sources.
Keywords :
backpropagation; fuzzy neural nets; power consumption; power engineering computing; FNN; back propagation learning algorithm; electric power consumption forecast; fuzzy neural network; life energy sources; Data models; Economics; Fuzzy control; Fuzzy neural networks; Power systems; Predictive models; Vectors; electric power consumption forecast of life energy sources; fuzzy integrated judge; fuzzy neural network;
Conference_Titel :
IT in Medicine and Education (ITME), 2011 International Symposium on
Conference_Location :
Cuangzhou
Print_ISBN :
978-1-61284-701-6
DOI :
10.1109/ITiME.2011.6130840
