DocumentCode
2953511
Title
Modelling the development of fluid dispensing for electronic packaging: Hybrid Particle Swarm Optimization based-wavelet neural network approach
Author
Ling, S.H. ; Iu, H.H.C. ; Leung, F.H.F. ; Chan, K.Y.
Author_Institution
Sch. of Electr., Electron., & Comput., Univ. of Western Australia, Perth, WA
fYear
2008
fDate
1-8 June 2008
Firstpage
98
Lastpage
103
Abstract
An hybrid particle swarm optimization PSO-based wavelet neural network for modelling the development of fluid dispensing for electronic packaging is presented in this paper. In modelling the fluid dispensing process, it is important to understand the process behaviour as well as determine optimum operating conditions of the process for a high-yield, low cost and robust operation. Modelling the fluid dispensing process is a complex non-linear problem. This kind of problem is suitable to be solved by neural network. Among different kinds of neural networks, the wavelet neural network is a good choice to solve the problem. In the proposed wavelet neural network, the translation parameters are variables depending on the network inputs. Thanks to the variable translation parameters, the network becomes an adaptive one. Thus, the proposed network provides better performance and increased learning ability than conventional wavelet neural networks. An improved hybrid PSO is applied to train the parameters of the proposed wavelet neural network. A case study of modelling the fluid dispensing process on electronic packaging is employed to demonstrate the effectiveness of the proposed method.
Keywords
electronic engineering computing; electronics packaging; neural nets; particle swarm optimisation; electronic packaging system; fluid dispensing process; hybrid particle swarm optimization; variable translation parameter; wavelet neural network approach; Electronics packaging; Feedforward neural networks; Feedforward systems; Function approximation; Genetic mutations; Industrial training; Manufacturing processes; Neural networks; Particle swarm optimization; Power system modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4633773
Filename
4633773
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