Fuzzy clustering of time series in the frequency domain
Information Sciences: an International Journal
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For overcoming the shortcoming that Fuzzy c-Means (FCM) clustering algorithm seriously depends on the ini- tial values of clustering numbers (c) and fuzzy exponent (m), we introduce genetic algorithm to find the pair param- eters of FCM simultaneity. In the proposed algorithm, the clustering numbers and the fuzzy exponent are controlled by a binary code. In order to optimize the two parame- ters, new methods to code, decode, crossover and establish fitness function have been proposed. Results demonstrat- ing the superiority of the proposed method, as compared to other method that only use validity index to find the clus- tering numbers (c), are provided for several real-life and artificial data sets.