Title :
Neural Network Research Using Particle Swarm Optimization
Author :
Wang, Yahui ; Xia, Zhifeng ; Huo, Yifeng
Author_Institution :
Sch. of Electron. & Inf. Eng., Beijing Univ. of Civil Eng. & Archit., Beijing, China
Abstract :
In view of the artificial neural network weights training problem, this paper proposed a method to optimize the network´s structure parameters and regularization coefficient using two-layer Particle Swarm Optimization (PSO). This algorithm was applied to train Adaline network. Compared with fixed regularization coefficient method and Sliding Mode Variable Structure optimization method, the result showed that it had the advantages of high precision and strong ability of generalization.
Keywords :
generalisation (artificial intelligence); learning (artificial intelligence); neural nets; particle swarm optimisation; variable structure systems; Adaline network; artificial neural network weight training problem; fixed regularization coefficient method; generalization; network structure parameter optimization; particle swarm optimization; sliding mode variable structure optimization method; Algorithm design and analysis; Educational institutions; Optimization; Particle swarm optimization; Signal processing algorithms; Testing; Training; Neural network; Regularization; Two-layer Particle Swarm;
Conference_Titel :
Internet Computing & Information Services (ICICIS), 2011 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-1561-7
DOI :
10.1109/ICICIS.2011.106
