Skip to main content
SpringerLink
Log in

Evolutionary Computation Applied to the Automatic Design of Artificial Neural Networks and Associative Memories

  • Conference paper
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 175))

Abstract

In this paper we describe how evolutionary computation can be used to automatically design artificial neural networks (ANNs) and associative memories (AMs). In the case of ANNs, Particle Swarm Optimization (PSO), Differential Evolution (DE), and Artificial Bee Colony (ABC) algorithms are used, while Genetic Programming is adopted for AMs. The derived ANNs and AMs are tested with several examples of well-known databases.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, J.A.: A simple neural network generating an interactive memory. Mathematical Biosciences 14, 197–220 (1972)

    Article  MATH  Google Scholar 

  2. Garro, B.A., Sossa, H., Vázquez, R.A.: Design of Artificial Neural Networks using a Modified Particle Swarm Optimization Algorithm. In: International Joint Conference on Neural Networks (IJCNN 2009), Atlanta, GE, USA, June 14-19, pp. 938–945 (2009)

    Google Scholar 

  3. Garro, B.A., Sossa, H., Vázquez, R.A.: Design of Artificial Neural Networks Using Differential Evolution Algorithm. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds.) ICONIP 2010, Part II. LNCS, vol. 6444, pp. 201–208. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  4. Garro, B.A., Sossa, H., Vázquez, R.A.: Evolving Neural Networks: A Comparison between Differential Evolution and Particle Swarm Optimization. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds.) ICSI 2011, Part I. LNCS, vol. 6728, pp. 447–454. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Garro, B.A., Sossa, H., Vázquez, R.A.: Artificial Neural Network Synthesis by means of Artificial Bee Colony (ABC) Algorithm. In: CEC 2011, New Orleans, June 5-8 (2011)

    Google Scholar 

  6. Garro, B.A., Sossa, H., Vázquez, R.A.: Back-Propagation vs Particle Swarm Optimization Algorithm: which Algorithm is better to adjust the Synaptic Weights of a Feed-Forward ANN? International Journal of Artificial Intelligence 7(11), 208–218 (2011)

    Google Scholar 

  7. Gurney, K.: An Introduction to Neural Networks. Taylor and Francis Group (1997)

    Google Scholar 

  8. Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization: Artificial Bee Colony (ABC) algorithm. Journal of Global Optimization 39(3), 459–471 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  9. Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. IV, pp. 1942–1948 (1995)

    Google Scholar 

  10. Kohonen, T.: Correlation matrix memories. IEEE Transactions on Computers C-21(4), 353–359 (1972)

    Article  Google Scholar 

  11. Koza, J.R.: Genetic Programming: A Paradigm for Genetically Breeding Populations of Computer Programs to Solve Problems, Stanford University Computer Science Department technical report (1990)

    Google Scholar 

  12. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press (1992)

    Google Scholar 

  13. Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press (1994)

    Google Scholar 

  14. Koza, J.R., Bennett, F.H., Andre, D., Keane, M.A.: Genetic Programming III: Darwinian Invention and Problem Solving. Morgan Kaufmann (1999)

    Google Scholar 

  15. McCulloch, W., Pitts, W.: A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics 7, 115–133 (1943)

    Article  MathSciNet  Google Scholar 

  16. Murphy, P.M., Aha, D.W.: UCI Repository of machine learning databases. University of California, Department of Information and Computer Science, Irvine, CA, US., Technical Report (1994)

    Google Scholar 

  17. Ritter, G., Dìaz, J.: Morphological associative memories. IEEE Transactions on Neural Networks 9(2), 281–293 (1998)

    Article  Google Scholar 

  18. Rosenblatt, F.: The Perceptron-a perceiving and recognizing automaton. Report 85-460-1, Cornell Aeronautical Laboratory (1957)

    Google Scholar 

  19. Rojas, R.: Neural networks - A systematic introduction. Chapter 7: The back propagation algorithm (1996)

    Google Scholar 

  20. Steinbuch, K.: Die Lernmatrix. Kybernetik 1(1), 36–45 (1961)

    Article  MATH  Google Scholar 

  21. Storn, R., Price, K.: Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 11, 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  22. Vazquez, R.A.: Izhikevich Neuron Model and its Application in Pattern Recognition. Australian Journal of Intelligent Information Processing Systems 11(1), 53–60 (2010)

    Google Scholar 

  23. Vázquez, R.A.: Pattern Recognition Using Spiking Neurons and Firing Rates. In: Kuri-Morales, A., Simari, G.R. (eds.) IBERAMIA 2010. LNCS, vol. 6433, pp. 423–432. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  24. Vazquez, R.A.: A computational approach for modelling the biological olfactory system during an odour discrimination task using spiking neuron. BMC Neuroscience 12(supp.1), 360 (2011)

    Article  Google Scholar 

  25. Vázquez, R.A., Garro, B.A.: Training Spiking Neurons by Means of Particle Swarm Optimization. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds.) ICSI 2011, Part I. LNCS, vol. 6728, pp. 242–249. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  26. Villegas, J., Sossa, H., Avilés, C., Olague, G.: Automatic Synthesis of Associative Memories by genetic Programming, a First Approach. Research in Computing Science 42, 91–102 (2009)

    Google Scholar 

  27. Villegas, J., Sossa, H., Avilés, C., Olague, G.: Automatic Synthesis of Associative Memories through Genetic Programming: a co-evolutionary approach. Revista Mexicana de Fsica 57(2), 110–116 (2011)

    Google Scholar 

  28. Yao, X.: A review of evolutionary artificial neural networks. Int. J. Intell. Syst. 8(4), 539–567 (1993)

    Article  Google Scholar 

  29. Yao, X.: Evolutionary artificial neural networks. In: Kent, A., Williams, J.G. (eds.) Encyclopedia of Computer Science and Technology, vol. 33, pp. 137–170. Marcel Dekker, New York (1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CIC-IPN, Juan de Dios Batiz S/N, Col. Nva. Industrial Vallejo, Mexico City, Mexico

    Humberto Sossa & Beatriz A. Garro

  2. UAM-Azcapotzalco, Av. San Pablo Xalpa 180. Azcapotzalco, Mexico City, Mexico

    Juan Villegas & Carlos Avilés

  3. CICESE, Carretera Ensenada-Tijuana, 3918Zona Playitas, Ensenada, B. C., Mexico

    Gustavo Olague

Authors
  1. Humberto Sossa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Beatriz A. Garro
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juan Villegas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gustavo Olague
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Carlos Avilés
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Humberto Sossa .

Editor information

Editors and Affiliations

  1. , Computer Science Department, CINVESTAV-IPN, Col. San Pedro Zacatenco 2508, Mexico City, 07360, Mexico

    Oliver Schütze

  2. , Computer Science Department, CINVESTAV-IPN, Col. San Pedro Zacatenco 2508, Mexico City, 07360, Mexico

    Carlos A. Coello Coello

  3. , Computer Science and Communications, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, 1359, Luxembourg

    Alexandru-Adrian Tantar

  4. Computer Science and Communications, Research Unit, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg

    Emilia Tantar

  5. Computer Science, and Communications, University of Luxembourg, rue Richard Coudenhove-Kalergi 6, Luxembourg, L-1359, Luxembourg

    Pascal Bouvry

  6. Bordeaux Mathematical Institute, INRIA Bordeaux-Sud Ouest, Université Bordeaux I, cours de la Libération 351, Talence Cedex, 33405, France

    Pierre Del Moral

  7. Bâtiment Leyteire, UFR Sciences et Modélisation, Université Bordeaux II, 3ter place de la Victoire, Bordeaux, 33000, France

    Pierrick Legrand

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sossa, H., Garro, B.A., Villegas, J., Olague, G., Avilés, C. (2013). Evolutionary Computation Applied to the Automatic Design of Artificial Neural Networks and Associative Memories. In: Schütze, O., et al. EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II. Advances in Intelligent Systems and Computing, vol 175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31519-0_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31519-0_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31518-3

  • Online ISBN: 978-3-642-31519-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation