期刊論文
| 學年 | 93 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2005-06-01 |
| 作品名稱 | An Efficient GA-Based Clustering Technique |
| 作品名稱（其他語言） | |
| 著者 | 林慧珍; Lin, Hwei-jen; Yang, Fu-wen; Kao, Yang-ta |
| 單位 | 淡江大學資訊工程學系 |
| 出版者 | 淡江大學 |
| 著錄名稱、卷期、頁數 | 淡江理工學刊=Tamkang journal of science and engineering 8(2), pp.113-122 |
| 摘要 | In this paper, we propose a GA-based unsupervised clustering technique that selects cluster centers directly from the data set, allowing it to speed up the fitness evaluation by constructing a look-up table in advance, saving the distances between all pairs of data points, and by using binary representation rather than string representation to encode a variable number of cluster centers. More effective versions of operators for reproduction, crossover, and mutation are introduced. Finally, the Davies-Bouldin index is employed to measure the validity of clusters. The development of our algorithm has demonstrated an ability to properly cluster a variety of data sets. The experimental results show that the proposed algorithm provides a more stable clustering performance in terms of number of clusters and clustering results. This results in considerable less computational time required, when compared to other GA-based clustering algorithms. |
| 關鍵字 | Unsupervised Clustering;Genetic Algorithms;Reproduction;Crossover;Mutation;Fitness;Cluster Validity |
| 語言 | en |
| ISSN | 1560-6686 |
| 期刊性質 | 國內 |
| 收錄於 | EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | TWN |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/45281 ) |