Modified Evolutionary Fuzzy Clustering
نویسنده
چکیده
In this paper, a novel modified evolutionary fuzzy clustering has been proposed. This technique exploits parameters such as Minkowski distance, Xie Beni index, and classification entropy. These parameters turn to account to polish the performance measure by incorporating shape of the cluster, class compactness and partitioning quality respectively in standard Fuzzy C-Means clustering. Moreover, we also employed an evolutionary strategy for optimizing fuzzy partition matrix. This avenue is examined over nine real world bench-mark problems of various domains. We ascertained that each problem sustains optimal result as compared to the conventional ones.
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تاریخ انتشار 2017