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《Gas Turbine Technology》 2010-04
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Gas Turbine Performance Calculation based on RBF Neural Networks

JIA Xiao-quan,ZHANG Ren-xing,HE Xing,FANG You-long (College of Naval Architecture and Power,Naval University of Engineering,Wuhan 430033,China)  
The components performance of gas turbine can be obtained by experiment,but it costs too much.Considering protection of the intellectual property rights,the manufactories don't provide the integrated curve of gas turbine.It will influence on precision of the model of gas turbine.Based on the segment curves of gas turbine which provided by the manufactory,some special data of gas turbine components performance were obtained by utilizing the radial basis function(RBF) neural networks which with the capability of multi-nonlinear,self-educated and generalization function in this paper.The results show that the RBF neural network obtain better effect of the train time and the precision of the training goal.The obtained integrated performance of the gas turbine is the groundwork for establishing the gas turbine simulation model and performance analysis.
【CateGory Index】: TK472;TP183
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