Group-based Particle Swarm Optimization with Communication Strategy Applied to Data Clustering
| Autor: | Ko-an Chu, 朱科安 |
|---|---|
| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 This study proposed a group-based particle swarm optimization abbreviated as GPSO, which the swarm is divided into subgroups and each subgroup communicated with each other. The GPSO was applied to the data clustering. Five types of communication strategies are tested in this study as follows: (1) each swarm subgroup exchange their best particles, (2) each swarm subgroup exchange their 20% of particles which are randomly selected, (3) assigning ranked particles (based on particle’s fitness) to each subgroup, (4) each swarm subgroup exchange their best 20% of particles, (5) combining approaches (2) and (3). This study used XB indicator, which measures the distance within and between each clusters, as the clustering performance index. This study conducted some experiments using some simulated and public UCI datasets. Our GPSO are better than the traditional PSO and K-mean clustering algorithm. Also, we found the communication strategy of combining the strategy of exchanging the best 20% particles with strategy of assigning the ranked particle performed better than the other four communication strategies. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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