CFP last date
20 March 2024
Call for Paper
April Edition
IJCA solicits high quality original research papers for the upcoming April edition of the journal. The last date of research paper submission is 20 March 2024

Submit your paper
Know more
Reseach Article

Analysis of a Nature Inspired Firefly Algorithm based Back-propagation Neural Network Training

by Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 22
Year of Publication: 2012
Authors: Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das
10.5120/6401-8339

Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das . Analysis of a Nature Inspired Firefly Algorithm based Back-propagation Neural Network Training. International Journal of Computer Applications. 43, 22 ( April 2012), 8-16. DOI=10.5120/6401-8339

@article{ 10.5120/6401-8339,
author = { Sudarshan Nandy, Partha Pratim Sarkar, Achintya Das },
title = { Analysis of a Nature Inspired Firefly Algorithm based Back-propagation Neural Network Training },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 22 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 8-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number22/6401-8339/ },
doi = { 10.5120/6401-8339 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:33:58.357664+05:30
%A Sudarshan Nandy
%A Partha Pratim Sarkar
%A Achintya Das
%T Analysis of a Nature Inspired Firefly Algorithm based Back-propagation Neural Network Training
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 22
%P 8-16
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Optimization algorithms are normally influenced by meta-heuristic approach. In recent years several hybrid methods for optimization are developed to find out a better solution. The proposed work using meta-heuristic Nature Inspired algorithm is applied with back-propagation method to train a feed-forward neural network. Firefly algorithm is a nature inspired meta-heuristic algorithm, and it is incorporated into back-propagation algorithm to achieve fast and improved convergence rate in training feed-forward neural network. The proposed technique is tested over some standard data set. It is found that proposed method produces an improved convergence within very few iteration. This performance is also analyzed and compared to genetic algorithm based back-propagation. It is observed that proposed method consumes less time to converge and providing improved convergence rate with minimum feed-forward neural network design

References
  1. Yang, X. S. , (2010) "Firefly Algorithm, Stochastic Test Functions and Design Optimisation", Int. J. Bio-Inspired Computation, Vol. 2, No. 2, pp. 78–84.
  2. X. -S. Yang, (2009)"Firefly algorithms for multimodal optimiza-tion", in: Stochastic Algorithms: Foundations and Applications, SAGA 2009, Lecture Notes in Computer Sciences, Vol. 5792, pp. 169-178 .
  3. X. -S. Yang, (2010) "Firefly algorithm, L´evy flights and global op-timization", in: Research and Development in Intelligent Systems XXVI (Eds M. Bramer, R. Ellis, M. Petridis), Springer London, pp. 209-218 .
  4. T. Apostolopoulos and A. Vlachos, "Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem",in: International Journal of Combinatorics,Vol. 2011, pp. 1-23.
  5. F. Tangour and P. Borne, (2008) "Presentation of some Meta-heuristic for the Optimization of complex system", in: Studies in Informatics and Control , Vol. 17, No. 2, pp. 169-180.
  6. H. Banati and M. Bajaj, (2011), "Fire Fly Based Feature Selection Approach", IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 4, No 2,pp. 473-480.
  7. N. Chai-ead, P. Aungkulanon*, and P. Luangpaiboon, 2011, "Bees and Firefly Algorithms for Noisy Non-Linear Optimisation Problems", International MultiConference of Engineers and Scientists (IMECS), Vol. II, Hong Kong.
  8. A. A. Abshouri and M. R. Meybodi, 2011, "New Firefly Algorithm based On Multi swarm & Learning Automata in Dynamic Environments", IEEE proceedings.
  9. A. Rajini, V. k. David, 2012, "A Hybrid Metaheuristic Algorithm for Classification using Micro array Data", International Journal of Scientific & Engineering Research, Vol. 3, Issue 2, pp. 1-9.
  10. UCI Machine Learning Repository : Iris Data Set - http://archive. ics. uci. edu/ml/datasets/Iris
  11. UCI Machine Learning Repository : Wine Data Set - http://archive. ics. uci. edu/ml/datasets/Wine
  12. UCI Machine Learning Repository : Liver Data Set - http://archive. ics. uci. edu/ml/datasets/Liver+Disorders
  13. M. T. Hagan and M. B. Menhaj, 1994, "Training feedforward networks with the Marquardt algorithm," IEEE Trans. Neural Netw. , vol. 5, no. 6, pp. 989–993.
  14. Samad, T. , 1990, "Back-propagation improvements based on heuristic arguments", Proceedings of International Joint Conference on Neural Networks, Washington, 1, pp. 565-568.
  15. David J. Montana and Lawrence Davis, 1989, "Training a Feed-forward Neural Networks using Genetic Algorithms", Journal of Machine Learning, pp. 762-767.
  16. C. Charalambous, 1992, "Conjugate gradient algorithm for efficient training of artificial neural networks", IEEE Proceedings, Vol. 139, No. 3, pp. 301-310.
Index Terms

Computer Science
Information Sciences

Keywords

Neural Network Back-propagation Firefly Back-propagation Algorithms Meta-heuristic Back-propagation