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 [1] 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.
Original language | English |
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Title of host publication | 2008 International Joint Conference on Neural Networks, IJCNN 2008 |
Pages | 98-103 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 24 Nov 2008 |
Event | 2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, Hong Kong Duration: 1 Jun 2008 → 8 Jun 2008 |
Conference
Conference | 2008 International Joint Conference on Neural Networks, IJCNN 2008 |
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Country/Territory | Hong Kong |
City | Hong Kong |
Period | 1/06/08 → 8/06/08 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence