Fuzzy Improved Genetic K-means Algorithm

Publish Year: 1390
نوع سند: مقاله کنفرانسی
زبان: English
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ICEE19_334

تاریخ نمایه سازی: 14 مرداد 1391

Abstract:

Clustering is a significant technique in data mining. Many methods for increasing the ability of clustering large data have been presented, one appropriate technique is the k-means method which has been combined with Artificial intelligence methods like genetic algorithm and has created an optimal performance. In primary clustering algorithms the clustering result depends on the initial centers of the clusters. In the presentation of an optimized clustering technique, apart from considering the current issues of clustering, it has tried to find the optimized number of clusters in the clustering procedure. The proposed technique increases the performance and integration of the k-means genetic algorithm with the use of fuzzy methods.

Authors

Arezo Bozorgnia

Dept. of Computer Engineering of Islamic Azad University of Mashhad

Samaneh Hajy Mahdizadeh Zargar

Dept. of Computer Engineering of Islamic Azad University of Mashhad

Mohammad.H Yaghmaee

Dept. of Computer Engineering of Islamic Azad University of Mashhad