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
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;
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
DOI :
10.1109/CISE.2009.5366684
