دانلود مقاله ISI انگلیسی شماره 46233
عنوان فارسی مقاله

خوشه بندی پویا با بهبود الگوریتم کلونی زنبور عسل مصنوعی باینری

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
46233 2015 12 صفحه PDF سفارش دهید 6940 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Dynamic clustering with improved binary artificial bee colony algorithm
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Soft Computing, Volume 28, March 2015, Pages 69–80

کلمات کلیدی
آنالیز خوشه ای - خوشه بندی به صورت خودکار - بهینه سازی گسسته - الگوریتم کلونی زنبور عسل دودویی
پیش نمایش مقاله
پیش نمایش مقاله خوشه بندی پویا با بهبود الگوریتم کلونی زنبور عسل مصنوعی باینری

چکیده انگلیسی

One of the most well-known binary (discrete) versions of the artificial bee colony algorithm is the similarity measure based discrete artificial bee colony, which was first proposed to deal with the uncapacited facility location (UFLP) problem. The discrete artificial bee colony simply depends on measuring the similarity between the binary vectors through Jaccard coefficient. Although it is accepted as one of the simple, novel and efficient binary variant of the artificial bee colony, the applied mechanism for generating new solutions concerning to the information of similarity between the solutions only consider one similarity case i.e. it does not handle all similarity cases. To cover this issue, new solution generation mechanism of the discrete artificial bee colony is enhanced using all similarity cases through the genetically inspired components. Furthermore, the superiority of the proposed algorithm is demonstrated by comparing it with the basic discrete artificial bee colony, binary particle swarm optimization, genetic algorithm in dynamic (automatic) clustering, in which the number of clusters is determined automatically i.e. it does not need to be specified in contrast to the classical techniques. Not only evolutionary computation based algorithms, but also classical approaches such as fuzzy C-means and K-means are employed to put forward the effectiveness of the proposed approach in clustering. The obtained results indicate that the discrete artificial bee colony with the enhanced solution generator component is able to reach more valuable solutions than the other algorithms in dynamic clustering, which is strongly accepted as one of the most difficult NP-hard problem by researchers.

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