A hybrid Evolutionary Functional Link Artificial Neural Network for Data mining and Classification

Abstract

This paper presents a specific structure of neural network as the functional link artificial neural network (FLANN). This technique has been employed for classification tasks of data mining. In fact, there are a few studies that used this tool for solving classification problems. In this present research, we propose a hybrid FLANN (HFLANN) model, where the optimization process is performed using 3 known population based techniques such as genetic algorithms, particle swarm and differential evolution. This model will be empirically compared to FLANN based back-propagation algorithm and to others classifiers as decision tree, multilayer perceptron based back-propagation algorithm, radical basic function, support vector machine, and K-nearest Neighbor. Our results proved that the proposed model outperforms the other single model. (Abstract)

Authors and Affiliations

Faissal MILI, Manel HAMDI

Keywords

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  • EP ID EP130191
  • DOI -
  • Views 104
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How To Cite

Faissal MILI, Manel HAMDI (2012). A hybrid Evolutionary Functional Link Artificial Neural Network for Data mining and Classification. International Journal of Advanced Computer Science & Applications, 3(8), 89-95. https://europub.co.uk./articles/-A-130191