Name
Abstract | ||
|---|---|---|
In this paper, an intelligent swarm based-wavelet neural network for affective mobile designed is presented. The contribution on this paper is to develop a new intelligent particle swarm optimization (iPSO), where a fuzzy logic system developed based on human knowledge is proposed to determine the inertia weight for the swarm movement of the PSO and the control parameter of a newly introduced cross-mutated operation. The proposed iPSO is used to optimize the parameters of wavelet neural network. An affective design of mobile phones is used to evaluate the effectiveness of the proposed iPSO. It has been found that significantly better results in a statistical sense can be obtained by the iPSO comparing with the existing hybrid PSO methods. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.neucom.2014.01.054 | Neurocomputing |
Keywords | Field | DocType |
new product development,particle swarm optimization | Particle swarm optimization,Wavelet neural network,Swarm behaviour,Multi-swarm optimization,Artificial intelligence,Mobile phone,Artificial neural network,Affective design,Mathematics,Machine learning,New product development | Journal |
Volume | Issue | ISSN |
142 | 1 | 0925-2312 |
Citations | PageRank | References |
4 | 0.39 | 17 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steve S. H. Ling | 1 | 8 | 3.50 |
| P. P. San | 2 | 4 | 0.39 |
| Kit Yan Chan | 3 | 470 | 45.36 |
| F. H. Frank Leung | 4 | 183 | 16.00 |
| Yiguang Liu | 5 | 338 | 37.15 |