文章基本信息

标题：The Clustering of Data Streams using Particle Swarm Optimization
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作者：Seydeh Somayeh Salehi Komamradkhi ; Saleh Shakeri ; Hamid Tavkolaei 等
期刊名称：International Journal of Mechatronics, Electrical and Computer Technology
印刷版ISSN：2305-0543
出版年度：2017
卷号：7
期号：26
页码：3685-3689
出版社：Austrian E-Journals of Universal Scientific Organization
摘要：Large volumes of data does not help the managers in decision-making and decision alone, but can also cause confusion managers of organizations. Therefore, managing the internal and external raw data and convert the data into information and knowledge using different techniques is very important and essential. The famous technique in the field of data mining, which can be done on the database and obtain the required knowledge. Explore clusters also one of the important techniques in growing fields, is known as data mining exploration that applied various disciplines of engineering and science, such as biology, psychology, medicine, marketing, computer and mapping satellite. The proposed methods are combination of two methods FCM and FKM. This improved to aid PSO and DCT. Studies show that the method presented in the paper is more efficient outcomes in terms of density and separation of clusters by minimizing the validity index XB. The PSO method is used in the paper for the optimum solutions and continuous and closest adjacent. In addition, the discrete cosine transform is used to reduce the dimensions and reduce the problem of search and more efficient for PSO.
关键词：clustering; data streams; DCT; FCM; PSO.