Training Product-Unit Neural Networks with Cuckoo Optimization Algorithm for Classification

Authors

  • Humar Kahramanli Selcuk University

DOI:

https://doi.org/10.18201/ijisae.2017533900

Keywords:

ANN, Classification, Cuckoo algorithm, PUNN.

Abstract

In this study Product-Unit Neural Networks (PUNN) which is the special class of feed-forward neural network, has been trained using Cuckoo Optimization algorithm. The trained model has been applied to two classification problem. BUPA liver disorders and Haberman's Survival Data have been used for application. The both data have been obtained from UCI machine Learning Repository. For comparison Backpropagation (BP) and Levenberg–Marquardt (LM) algorithms have been used. The application results show that the PUNN trained with Cuckoo Optimization algorithm is achieved better classification accuracy.

Downloads

Download data is not yet available.

References

S. Alwaisi, Ö. K. Baykan, “Training Of Artificial Neural Network Using Metaheuristic Algorithm”, International Journal of Intelligent Systems and Applications in Engineering, IJISAE, Special Issue, 12–16.

S. Mukhopadhyay, C. Tang, J. Huang, M. Yu, M. Palakal, “A comparative study of genetic sequence classification algorithms”, Neural networks for signal processing. In Proceedings of the 2002 12th IEEE workshop on 4–6 September 2002, pp. 57–66.

C. Hervás, F. J. Martínez, P. A. Gutiérrez, “Classification by means of Evolutionary Product-Unit Neural Networks”, 2006 International Joint Conference on Neural Networks Sheraton Vancouver Wall Centre Hotel, Vancouver, BC, Canada July 16-21, 2006.

de N. Arie, M. Erwin, S. Sebastiaan, "Accurate Prediction Of Ecological Quality Ratio With Product Unit Neural Networks" , CUNY Academic Works, 2014.

A. Guerrero-Enamorado, D. Ceballos-Gastell, “An Experimental Study of Evolutionary Product-Unit Neural Network Algorithm”, Computación y Sistemas, Vol. 20, No. 2, 2016, pp. 205–218, doi: 10.13053/CyS-20-2-2218

C. Zhang, W. Wu, X. H. Chen, Y. Xiong, “Convergence of BP algorithm for product unit neural networks with exponential, weights, Neurocomputing”, Volume 72, Issues 1–3, Pp 513-520, 2008.

A. Martı´nez-Estudillo, F. Martı´nez-Estudillo, C. Herva´s-Martı´nez, N. Garcı´a-Pedrajas, “Evolutionary product unit based neural networks for regression”, Neural Networks 19, 477–486, 2006.

K. Dulakshi, A. W. Jayawardena and W. K. Li, “Evolutionary product unit based neural networks for hydrological time series analysis”, Journal of Hydroinformatics, 13.4, 2011.

F.J. Martı´nez-Estudillo, C. Herva´s-Martı´nez, P. A. Gutie´rrez, A. C. Martı´nez-Estudillo, “Evolutionary product-unit neural networks classifiers”, Neurocomputing 72, 548–561, 2008.

R. Rajabioun, “Cuckoo Optimization Algorithm”, Applied Soft Computing, Volume 11, Issue 8, pp. 5508-5518, 2011.

M. Lichman, UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science, last accessed 15.08.2017.

Downloads

Published

12.12.2017

How to Cite

Kahramanli, H. (2017). Training Product-Unit Neural Networks with Cuckoo Optimization Algorithm for Classification. International Journal of Intelligent Systems and Applications in Engineering, 5(4), 252–255. https://doi.org/10.18201/ijisae.2017533900

Issue

Section

Research Article