| Fingerprint recognition by multi-objective optimization PSO hybrid with SVM | |
|---|---|
| 學年 | 103 |
| 學期 | 1 |
| 出版（發表）日期 | 2014-12-01 |
| 作品名稱 | Fingerprint recognition by multi-objective optimization PSO hybrid with SVM |
| 作品名稱（其他語言） | |
| 著者 | Hsieh, Ching-Tang; Hu, Chia-Shing |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Mexico: Universidad Nacional Autonoma de Mexico * Centro de Ciencias Aplicadas y Desarrollo Tecnologico |
| 著錄名稱、卷期、頁數 | Journal of Applied Research and Technology 12(6), pp.1014-1024 |
| 摘要 | Researchers put efforts to discover more efficient ways to classification problems for a period of time. Recent years,the support vector machine (SVM) becomes a well-popular intelligence algorithm developed for dealing this kind of problem. In this paper, we used the core idea of multi-objective optimization to transform SVM into a new form. This form of SVM could help to solve the situation: in tradition, SVM is usually a single optimization equation, and parameters for this algorithm can only be determined by user’s experience, such as penalty parameter. Therefore, our algorithm is developed to help user prevent from suffering to use this algorithm in the above condition. We use multiobjective Particle Swarm Optimization algorithm in our research and successfully proved that user do not need to use trial – and – error method to determine penalty parameter C. Finally, we apply it to NIST-4 database to assess our proposed algorithm feasibility, and the experiment results shows our method can have great results as we expect. |
| 關鍵字 | MOPSO-CD;SVM;fingerprint recognition |
| 語言 | en |
| ISSN | 1665-6423 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | Hu, Chia-Shing |
| 審稿制度 | 是 |
| 國別 | MEX |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/100117 ) |
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