DocumentCode
572925
Title
Vehicle simulation and test system based on RBFNN and its improved algorithm
Author
Jiang, Yicheng ; Sun, Sibo
Author_Institution
Dept. of Electron. Eng., Harbin Inst. of Technol., Harbin, China
fYear
2012
fDate
24-26 Aug. 2012
Firstpage
790
Lastpage
794
Abstract
According to the characteristics of the vehicle simulation and test system, we set up the vehicle acceleration and engine speed model, and RBF neural network is applied in this model. Since ordinary RBF network has poor adaptability, NRBF and Classified-RBF is proposed in this paper. The simulation results show that both methods can fit the model well, and the output error actually decreases to about half. The adaptability of the RBF network is improved. These can be used in the data fusion of the vehicle simulation and test system.
Keywords
automobile industry; engines; radial basis function networks; simulation; testing; vehicles; RBF neural network; RBFNN; classified-RBF; engine speed model; test system; vehicle acceleration; vehicle simulation; Adaptation models; Classification algorithms; Engines; Training; Vehicles; NRBF; RBF neural network; simulation; vehicle test system;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Processing (CSIP), 2012 International Conference on
Conference_Location
Xi´an, Shaanxi
Print_ISBN
978-1-4673-1410-7
Type
conf
DOI
10.1109/CSIP.2012.6308972
Filename
6308972
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