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

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)

@article{MILI2012,
  title     = {A hybrid Evolutionary Functional Link Artificial Neural Network for Data mining and Classification},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {3},
  number    = {8},
  year      = {2012},
  publisher = {The Science and Information Organization},
  author    = {Faissal MILI and Manel HAMDI},
  doi       = {10.14569/IJACSA.2012.030815},
  url       = {https://doi.org/10.14569/IJACSA.2012.030815}
}