DocumentCode
508322
Title
Based on RBF Neural Network of the Heat Load Forecasting and Research
Author
Gao, Jun-ru ; Meng, Xin ; Zhang, Zheng
Author_Institution
Hebei Univ. of Eng., Handan, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
The load forecast is the foundation of optium control for heating system. This paper systematicaly discussed the application research of heating system predication which adopted the fuzzy neural networks technology. RBF neural networks are constructed by MATLAB. This method is characterized by higher computing accuracy and fast convergence velocity, it is very suitable in the engineering and may greatly enhance the automation of central heating system and energy-saving effects.
Keywords
fuzzy neural nets; heat systems; load forecasting; power engineering computing; radial basis function networks; RBF neural network; central heating system; energy-saving effect; fuzzy neural network; heat load forecasting; Automation; Control systems; Fuzzy control; Fuzzy neural networks; Heating; Load forecasting; MATLAB; Neural networks; Power engineering and energy; Temperature control;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5366684
Filename
5366684
Link To Document