Title :
Application research of three layer BP network on performance evaluation of wet cooling tower under cross-wind conditions
Author :
Gao, Ming ; Sun, Fengzhong ; Gong, Tingting ; Wang, Nini
Author_Institution :
Energy Source of Power Eng., Shandong Univ. (SDU), Jinan, China
Abstract :
Based on the level Froude number (Frl), A three-layer back propagation (BP) network model which has one hidden layer is developed, and the node number in the input layer, hidden layer and output layer are 4, 8 and 6, respectively. This model adopts the improved BP algorithm, that is, the gradient descent method with momentum. This BP predicted model demonstrated a good statistical performance with the MRE and R in the range of 0.48%-3.92% and 0.992-0.999, respectively, and the RMSE values for the ANN training and predictions were very low relative to the range of the experiments. Because the level Froude number is involved, this BP network model can be used to predict the thermal performance of prototype tower in large-scale power plants, and providing the theoretical basis on the research of heat and mass transfer inside cooling tower under cross-wind conditions in power plants.
Keywords :
backpropagation; cooling towers; gradient methods; heat transfer; mass transfer; performance evaluation; ANN training; BP network; Froude number; backpropagation network model; gradient descent method; heat transfer; mass transfer; performance evaluation; statistical performance; wet cooling tower; Artificial neural networks; Cooling; Heat transfer; Poles and towers; Power generation; Predictive models; Training; BP model; Cross-wind; Froude number; Performance evaluation;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5582973