A Hybrid Fuzzy Firefly Based Evolutionary Radial Basis Functional Network for Classification

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Provided by: International Journal of Information Processing
Topic: Networking
Format: PDF
In this paper, a hybrid evolutionary fuzzy firefly based Radial Basis Function (RBF) network has been designed to classify the real world data. The paper is comprised of two stages: first, the Fuzzy C-Means (FCM) algorithm is applied with to get effective data points and then those data points have been inputted to the RBFN network for effective classification. The weights of RBF network are updated by using the firefly algorithm. The determination of centers of RBF units strongly affects the performance of a Radial Basis Function network. Various clustering algorithms like K-means and fuzzy c-means algorithms are widely used to determine the location of centers of RBF units.
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