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Computational Intelligence and Neuroscience
Volume 2017, Article ID 2157852, 9 pages
https://doi.org/10.1155/2017/2157852
Research Article

Application of the Intuitionistic Fuzzy InterCriteria Analysis Method with Triples to a Neural Network Preprocessing Procedure

1Laboratory of Intelligent Systems, University “Prof. Dr. Assen Zlatarov”, 1 “Prof. Yakimov” Blvd., 8010 Burgas, Bulgaria
2Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, 105 “Acad. G. Bonchev” Str., 1113 Sofia, Bulgaria
3Department of Intelligent Systems, Institute of Information and Communication Technologies, 2 “Acad. G. Bonchev” Str., 1113 Sofia, Bulgaria

Correspondence should be addressed to Sotir Sotirov; gb.utb@voritoss

Received 9 February 2017; Accepted 14 June 2017; Published 10 August 2017

Academic Editor: George A. Papakostas

Copyright © 2017 Sotir Sotirov et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Bellis, K. M. Razeeb, C. Saha et al., “FPGA implementation of spiking neural networks - An initial step towards building tangible collaborative autonomous agents,” in Proceedings of the 2004 IEEE International Conference on Field-Programmable Technology, FPT '04, pp. 449–452, December 2004. View at Scopus
  2. S. Himavathi, D. Anitha, and A. Muthuramalingam, “Feedforward neural network implementation in FPGA using layer multiplexing for effective resource utilization,” IEEE Transactions on Neural Networks, vol. 18, no. 3, pp. 880–888, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. D. M. Karantonis, M. R. Narayanan, M. Mathie, N. H. Lovell, and B. G. Celler, “Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring,” IEEE Transactions on Information Technology in Biomedicine, vol. 10, no. 1, pp. 156–167, 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Haykin, Neural Networks: A Comprehensive Foundation, NY: Macmillan, 1994.
  5. Z.-L. Gaing, “Wavelet-based neural network for power disturbance recognition and classification,” IEEE Transactions on Power Delivery, vol. 19, no. 4, pp. 1560–1568, 2004. View at Publisher · View at Google Scholar · View at Scopus
  6. M. Meissner, M. Schmuker, and G. Schneider, “Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training,” BMC Bioinformatics, vol. 7, article 125, 2006. View at Publisher · View at Google Scholar · View at Scopus
  7. S. Sotirov, V. Atanassova, E. Sotirova, V. Bureva, and D. Mavrov, “Application of the intuitionistic fuzzy InterCriteria analysis method to a neural network preprocessing procedure,” in Proceedings of the 16th World Congress of the International Fuzzy Systems Association (IFSA) 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), pp. 1559–1564.
  8. J. M. Zurada, A. Malinowski, and I. Cloete, “Sensitivity analysis for minimization of input data dimension for feedforward neural network,” in Proceedings of the 1994 IEEE International Symposium on Circuits and Systems. Part 3 (of 6), pp. 447–450, June 1994. View at Scopus
  9. M. Lin, Q. Chen, and S. Yan, “Network in network,” arXiv preprint arXiv:1312.4400, 2013.
  10. K. Atanassov, D. Mavrov, and V. Atanassova, “InterCriteria decision making. A new approach for multicriteria decision making, based on index matrices and intuitionistic fuzzy sets,” in Issues in IFS and GN, p. 11, 11, 1–7, 2014. View at Google Scholar
  11. K. T. Atanassov, “Intuitionistic fuzzy sets,” Fuzzy Sets and Systems, vol. 20, no. 1, pp. 87–96, 1986. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  12. K. Atanassov, Intuitionistic Fuzzy Sets: Theory and Applications, Physica-Verlag, Heidelberg, Germany, 1999. View at Publisher · View at Google Scholar · View at MathSciNet
  13. K. T. Atanassov, “Intuitionistic Fuzzy Relations (IFRs),” in On Intuitionistic Fuzzy Sets Theory, vol. 283 of Studies in Fuzziness and Soft Computing, pp. 147–193, Springer Berlin Heidelberg, Berlin, Heidelberg, 2012. View at Publisher · View at Google Scholar
  14. L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965. View at Publisher · View at Google Scholar · View at Scopus
  15. K. T. Atanassov, Index matrices: towards an augmented matrix calculus, vol. 573 of Studies in Computational Intelligence, Springer, Cham, 2014. View at Publisher · View at Google Scholar · View at MathSciNet
  16. K. Atanassov, V. Atanassova, and G. Gluhchev, “InterCriteria analysis: ideas and problems,” in Notes on Intuitionistic Fuzzy Sets, vol. 21, pp. 81–88, 1 edition, 2015. View at Google Scholar
  17. V. Atanassova, L. Doukovska, A. Michalíková, and I. Radeva, “Intercriteria analysis: from pairs to triples,” Notes on Intuitionistic Fuzzy Sets, vol. 22, no. 5, pp. 98–110, 2016. View at Google Scholar
  18. V. Atanassova, D. Mavrov, L. Doukovska, and K. Atanassov, “Discussion on the threshold values in the InterCriteria decision making approach,” Notes on Intuitionistic Fuzzy Sets, vol. 20, no. 2, pp. 94–99, 2014. View at Google Scholar
  19. M. Hagan, H. Demuth, and M. Beale, Neural Network Design, PWS Publishing, Boston, MA, USA, 1996.
  20. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature, vol. 323, no. 6088, pp. 533–536, 1986. View at Publisher · View at Google Scholar · View at Scopus
  21. S. Krumova, S. Todinova, D. Mavrov et al., “Intercriteria analysis of calorimetric data of blood serum proteome,” Biochimica et Biophysica Acta (BBA) - General Subjects, vol. 1861, no. 2, pp. 409–417, 2017. View at Publisher · View at Google Scholar
  22. S. Todinova, D. Mavrov, S. Krumova et al., “Blood plasma thermograms dataset analysis by means of intercriteria and correlation analyses for the case of colorectal cancer,” International Journal Bioautomation, vol. 20, no. 1, pp. 115–124, 2016. View at Google Scholar · View at Scopus
  23. D. S. Stratiev, S. Sotirov, I. Shishkova et al., “Investigation of relationships between bulk properties and fraction properties of crude oils by application of the intercriteria analysis,” Petroleum Science and Technology, vol. 34, no. 13, pp. 1113–1120, 2016. View at Publisher · View at Google Scholar · View at Scopus