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Fuzzy Clustering Based On Forest Optimization Algorithm

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Chaghari, Arash (Author)
مؤلفين آخرين: Feizi-Derakhshi, Mohammad-Reza (Co-Author) , Balafar, Mohammad-Ali (Co-Author)
المجلد/العدد: مج30, ع1
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2018
الصفحات: 25 - 32
DOI: 10.33948/0584-030-001-003
ISSN: 1319-1578
رقم MD: 974293
نوع المحتوى: بحوث ومقالات
اللغة: English
قواعد المعلومات: science
مواضيع:
علوم الحاسوب | الخوارزميات | تحليل البيانات | الخوارزميات الجينية
كلمات المؤلف المفتاحية:
Fuzzy Clustering | Partition Matrix | Forest Optimization | Gradient Method | Clustering Index
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المستخلص: Clustering is one of the classification methods for data analysis and it is one of the ways of data analysis, too. There are various methods for fuzzy clustering using optimization algorithms such as genetic algorithm and particle swarm optimization algorithm that were specified. In this paper, the combination of one of the recent optimization algorithms called Forest optimization algorithm and one of the local search methods called gradient method are used to perform fuzzy clustering. The purpose of applying the gradient method is accelerating the convergence of the used optimization algorithm. To apply the proposed method, 4 types of real data sets are used. Cluster validity measures are used to obtain and verify the accuracy of the proposed method (FOFCM). By analyzing and comparing the results of the proposed method with the results of algorithms GGAFCM (fuzzy clustering based on genetic algorithm) and PSOFCM (fuzzy clustering based on particle swarm optimization algorithm), it has been shown that the accuracy of the proposed approach is significantly increased.
ISSN: 1319-1578

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