Fuzzy Improved Genetic K-means Algorithm
Publish place: 19th Iranian Conference on Electric Engineering
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.
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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