کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
411956 679598 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A dynamic shuffled differential evolution algorithm for data clustering
ترجمه فارسی عنوان
الگوریتم تکاملی دیافراگم پویا برای خوشه بندی داده ها
کلمات کلیدی
تکامل دیفرانسیل، طرح توجیهی، مبادله اطلاعات، تکنیک اولیه رمان، خوشه بندی داده ها
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

In order to further improve the convergence performance of data clustering algorithms, a dynamic shuffled differential evolution algorithm, DSDE for short, is presented in this paper. In DSDE, mutation strategy DE/best/1 is employed, which can take advantage of the direction guidance information of best individual so as to speed up the corresponding algorithm. Meanwhile, inspired by shuffled frog leaping algorithm, a sorting scheme and a randomly shuffled scheme are used to divide a total population into two subpopulations during the evolving process. In this way, mutation strategy DE/best/1 is actually used in two subpopulations, respectively, which can effectively exchange information between two subpopulations and balance the exploitation ability of DE/best/1/bin. In addition, most popular data clustering algorithms suffer from the choice of initial clustering centers, which may cause a premature convergence. Here a novel initial technique, called the random multi-step sampling, is integrated into DSDE to overcome the shortcoming. Then an experiment tested on 11 well-known datasets has been carried out, and the related results demonstrate that DSDE significantly outperforms DE/rand/1/bin and DE/best/1/bin. Next, another comparison among DSDE and other four well-known data clustering algorithms is conducted. The related results also show that DSDE is superior to other four approaches including particle swarm optimization with age-group topology (PSOAG) in terms of objective function value, i.e., the sum of intra-cluster distance. In a word, all the experimental results confirm that the proposed algorithm DSDE can be considered as an excellent tool for data clustering.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 158, 22 June 2015, Pages 144–154
نویسندگان
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