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It accords with the human's intelligence for data processing that we do information granulation of time series and then study and analyze the time series on the different level of granularities. There are two kinds of traditional methods for the information granulation of temporal data. One implements the granulation by first dividing the time series into segments in terms of the granularity of the...
Fuzzy c-means plays an important role in investigating the structure of dataset. In order to clustering the temporal or spatial dataset, constraints-equipped version of fuzzy c-means was proposed in literature. This paper focuses on the clustering of temporal dataset, and presents a new version of constraints-equipped fuzzy c-means algorithm, where the temporal constraints are described by fuzzy sets...
This paper focuses on the conditional fuzzy inference sentence "if x is a, then y is b, else y is c", and presents a new method for determining it true value domain. Instead of transforming the problem into solving a system of two fuzzy relation equations, the new method transforms the original problem into solving a system of four fuzzy relation equations. We give out the necessary and...
Horizontal collaboration fuzzy C-means (HC-FCM) is a useful tool for dealing with collaborative clustering problems where a pattern-set is described in some different feature spaces independently and thus results in different data sets. By means of FCM, clustering may be carried on these different data sets and thus result in different partition matrices. For one of these data sets, how to take means...
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