Abstract
Particle Swarm Optimization is a new population based optimization methodology. With a characteristic of high performance and easy implementation, the Particle Swarm Optimizer has many successful cases. However, it still has a problem of efficiency in solving sequential problems. In this paper, we propose a more efficient discrete particle swarm algorithm in solving the sequential problems such as graphic presentation of GMDH network. The dataset of Fisher's Iris Plant is tested, and the results are shown.
| Original language | English |
|---|---|
| Pages (from-to) | 2329-2333 |
| Number of pages | 5 |
| Journal | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 3 |
| State | Published - 2005 |
| Event | IEEE Systems, Man and Cybernetics Society, Proceedings - 2005 International Conference on Systems, Man and Cybernetics - Waikoloa, HI, United States Duration: 10 10 2005 → 12 10 2005 |
Keywords
- Group Method of Data Handling (GMDH)
- Particle Swarm Optimization (PSO)
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