Ant based algorithms have proved to be very efficient for solving real problems. These algorithms emphasize flexibility, robustness and decentralized control. Thus more and more researches are interested in this new way of designing intelligent systems in which centralization, control and preprogramming are replaced with self-organization, emergence and autonomy. In this context, many ant based algorithms have been proposed for data clustering problem. The purpose of this paper is to present a new intelligent approach for data clustering problem based on social insect metaphor and FCM algorithm.
CITATION STYLE
Hamdi, A., Monmarché, N., Slimane, M., & Alimi, A. M. (2017). Intelligent hybrid algorithm for unsupervised data clustering problem. In Advances in Intelligent Systems and Computing (Vol. 552, pp. 442–455). Springer Verlag. https://doi.org/10.1007/978-3-319-52941-7_44
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