Jiashun Chen

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This paper analyzes sensitivity of Fuzzy C-means to noisy which generates unreasonable clustering results. We also find that Fuzzy C-means possess monotonicity, which may generate meaningless clustering results. Aiming at these weak points, we present an improved Fuzzy C-means named IFCM (Improved Fuzzy C-means). Firstly, we research the reason of(More)
Aiming at the weak points of fuzzy cluster validity indexes that measure compactness within cluster and separation between clusters based on distance, we propose a new non-distance cluster index. Firstly, we analyze that validity index based on distance can't recognize overlapping clusters and is sensitive to noisy data. Secondly, we measure compactness(More)
In this paper, we proposed a new trajectory clustering based on partition-cluster-extract (PCE). Firstly, some relative definitions are defined, and then we proposed a new partition method named PCE, which is based on method of partition-group framework. Finally, on the basis of PCE and relative definitions, we proposed a new algorithm named(More)
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