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论文类型：期刊论文
发表时间：2010-01-01
发表刊物：Journal of Information and Computational Science
收录刊物：EI、Scopus
卷号：7
期号：1
页面范围：119-125
摘要：The feather vector set with higher dimensionality causes the worse convergency to realistic in practice using the conventional fuzzy C-means algorithm. In this paper, a novel algorithm called the fuzzy C-means based on Entropy Coding, FCM-EC, is realized by adding a powerful method based on entropy coding to the conventional fuzzy C-means algorithm. And it is applied to classify the traffic state with a high-dimensional feature set space. Experimental results on real traffic data show that the FCM-EC has better performance and robust than the conventional fuzzy C-means algorithm when the feature set space is high-dimensional. Copyright ? 2010 Binary Information Press.