| Autor: |
Hsiang-Chuan Liu, Der-Bang Wu, Jeng-Ming Yih, Shin-Wu Liu |
| Rok vydání: |
2008 |
| Předmět: |
|
| Zdroj: |
2008 International Workshop on Education Technology and Training & 2008 International Workshop on Geoscience and Remote Sensing. |
| Popis: |
The popular fuzzy c-means algorithm (FCM) converges to a local minimum of the objective function. Hence, different initializations may lead to different results. The important issue is how to avoid getting a bad local minimum value to improve the cluster accuracy. The particle swarm optimization (PSO) is a popular and robust strategy for optimization problems. But the main difficulty in applying PSO to real-world applications is that PSO usually need a large number of fitness evaluations before a satisfying result can be obtained. In this paper, the improved new algorithm, ldquoFuzzy C-Mean based on Picard iteration and PSO (PPSO-FCM)rdquo, is proposed. Two real data sets were applied to prove that the performance of the PPSO-FCM algorithm is better than the conventional FCM algorithm and the PSO-FCM algorithm. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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