کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
385841 660873 2011 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A novel hybrid K-harmonic means and gravitational search algorithm approach for clustering
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A novel hybrid K-harmonic means and gravitational search algorithm approach for clustering
چکیده انگلیسی

Clustering is used to group data objects into sets of disjoint classes called clusters so that objects within the same class are highly similar to each other and dissimilar from the objects in other classes. K-harmonic means (KHM) is one of the most popular clustering techniques, and has been applied widely and works well in many fields. But this method usually runs into local optima easily. A hybrid data clustering algorithm based on an improved version of Gravitational Search Algorithm and KHM, called IGSAKHM, is proposed in this research. With merits of both algorithms, IGSAKHM not only helps the KHM clustering to escape from local optima but also overcomes the slow convergence speed of the IGSA. The proposed method is compared with some existing algorithms on seven data sets, and the obtained results indicate that IGSAKHM is superior to KHM and PSOKHM in most cases.

Research highlights
► IGSA is introduced to enhance the global search ability.
► IGSA is integrated into KHM to form a hybrid clustering algorithm.
► Experimental results show the algorithm outperforms most state-of-art algorithms.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 38, Issue 8, August 2011, Pages 9319–9324
نویسندگان
, , , , ,