A Review on Gravitational Search Algorithm and its Applications to Data Clustering & Classification

Автор: Yugal kumar, G. Sahoo

Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa

Статья в выпуске: 6 vol.6, 2014 года.

Бесплатный доступ

Natural phenomenon’s and swarms behavior are the warm area of research among the researchers. A large number of algorithms have been developed on the account of natural phenomenon’s and swarms behavior. These algorithms have been implemented on the various computational problems for the sake of solutions and provided significant results than conventional methods but there is no such algorithm which can be applied for all of the computational problems. In 2009, a new algorithm was developed on the behalf of theory of gravity and was named gravitational search algorithm (GSA) for continuous optimization problems. In short span of time, GSA algorithm gain popularity among researchers and has been applied to large number of problems such as clustering, classification, parameter identification etc. This paper presents the compendious survey on the GSA algorithm and its applications as well as enlightens the applicability of GSA in data clustering & classification.

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Classification, Clustering, Gravitational Search Algorithm, Optimization, Nature Inspired Algorithm

Короткий адрес: https://sciup.org/15010573

IDR: 15010573

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