Title :
The recognition of train wheel tread damages based on PSO-RBFNN algorithm
Author :
Zhao Yong ; Ye Hong ; Kang Zheng-sheng ; Shi Song-shan ; Zhou Lin
Author_Institution :
Mech. Dept., Chang´an Univ., Xi´an, China
Abstract :
In order to the recognition of the train wheel tread damages, the pattern recognition method of the train wheel tread damages based on PSO-RBFNN was developed. The algorithm uses PSO-RBFNN algorithm to optimize center and spread of RBFNN, the connection weight value is sovled by least squares method. Compared with the traditional RBFNN,BP and GA-RBFNN, the experiment results show that the recognition rate of testing samples is higher than the traditional RBFNN, BP and GA-RBFNN, the evolutional generations of PSO-RBFNN algorithm were less than RBFNN, BP and GA-RBFNN.
Keywords :
least squares approximations; particle swarm optimisation; pattern recognition; radial basis function networks; railway engineering; wheels; BP; GA-RBFNN; PSO-RBFNN algorithm; connection weight value; least squares method; pattern recognition; train wheel tread damages; Accuracy; Feature extraction; Inspection; Pattern recognition; Signal processing algorithms; Training; Wheels; PSORBFNN; recognition; train wheel; tread damage;
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-2130-4
DOI :
10.1109/ICNC.2012.6234662