Open Access
MATEC Web Conf.
Volume 125, 2017
21st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017)
Article Number 02061
Number of page(s) 4
Section Systems
Published online 04 October 2017
  1. Zelinka I., Vařacha P., Oplatková Z., Volná E. Structural Synthesis of Neural Network by Means of Analytic Programmig. In 12th International Conference on Soft Computing. Czech Republic, VUT Brno, p. 25–30 (2006) [Google Scholar]
  2. Vařacha P. Neural Network Synthesis Dealing with Classification Problem. In Recent Researches in Automatic Control. Montreux: WSEAS Press, p. 377–382 (2011) [Google Scholar]
  3. Šenkerik R., Zelinka I., Davendra D., Oplatkova Z. Utilization of SOMA and differential evolution for robust stabilization of chaotic Logistic equation, Computers & Mathematics with Applications, Volume 60, Issue 4, Pages 1026–1037, ISSN 0898-1221, doi 10.1016/j.camwa.2010.03.059. (2010) [CrossRef] [Google Scholar]
  4. Šenkeřík R. Oplatkova Z., Zelinka I, Davendra D., Synthesis of feedback controller for three selected chaotic systems by means of evolutionary techniques: Analytic programming, Mathematical and Computer Modelling, ISSN 0895-7177, 10.1016/j.mcm.2011.05.030 (Available online 27 May 2011) [Google Scholar]
  5. Vařacha P., Zelinka I. Analytic Programming Powered by Distributed Self-Organizing Migrating Algorithm Application. In IEEE Proceedings 7th International Conference Computer Information Systems and Industrial Management Applications. Ostrava: IEEE Computer Society, p. 99–100 (2008) [Google Scholar]
  6. Prechelt L., Proben1—A Set of Neural Network Benchmark Problems and Benchmarking Rules, Universität Karlsruhe, Germany (1994) [Google Scholar]
  7. Mangarianm O.L., Wolberg W.H., Cancer diagnosis via linear programming, SIAM News, Volume 23, Number 5,, p. 1–18 (1990) [Google Scholar]
  8. Král E., Dolinay V., Vašek L., Vařacha P. Usage of PSO Algorithm for Parameters Identification of District Heating Network Simulation Model. In 14th WSEAS International Conference on Systems. Latest Trands on Systems. Volume II, Rhodes, WSEAS Press (GR). p. 657–659 (2010) [Google Scholar]
  9. Chramcov Bronislav. Identification of time series model of heat demand using Mathematica environment. In Recent Researches in Automatic Control. Montreux: WSEAS Press, s. 346–351 (2011) [EDP Sciences] [Google Scholar]
  10. Zelinka I., Studies in Fuzziness and Soft Computing, New York: Springer-Verlag, (2004) [Google Scholar]
  11. Koza J. R., Genetic Programming, MIT Press, ISBN 0-262-11189-6 (1998) [Google Scholar]
  12. Jui-Yu W., MIMO CMAC neural network classifier for solving classification problems, Applied Soft Computing, Volume 11, Issue 2, The Impact of Soft Computing for the Progress of Artificial Intelligence, p. 2326–2333 (2011) [Google Scholar]
  13. Falco D.I., Cioppa E., Tarantino, Discovering interesting classification rules with genetic programming, Applied Soft Computing 1, p. 257–269 (2002) [CrossRef] [Google Scholar]
  14. Brameier M., Banzhaf W., A comparison of linear genetic programming and neural networks in medical data mining, IEEE Transactions on Evolutionary [Google Scholar]
  15. Turner et al., Grammatical Evolution of Neural Networks for Discovering Epistasis among Quantitative Trait Loci Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics Book Series Title: Lecture Notes in Computer Science Publisher: Springer Berlin / Heidelberg, p: 86–97 (2010) [Google Scholar]
  16. Vonk E., Jain L.C., Johnson R.P., Automatic Generation of Neural Network Architecture Using Evolutionary Computation, Advances in Fuzzy Systems – Applications and Theory, Volume 14, World Science, ISBN: 981–02–3106–7 (1997) [CrossRef] [Google Scholar]
  17. Koza J. R. et al. Genetic Programming III; Darwinian Invention and problem Solving, Morgan Kaufmann Publisher, (1999) [Google Scholar]

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