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Year 2018, Volume: 3 Issue: 1, 5 - 8, 01.12.2018

Abstract

References

  • [1] M. A. Kramer, “Autoassociative neural networks,” Computers & Chemical Engineering, vol. 16, 1992, pp. 313-328.
  • [2] G. Desjardins, R. Proulx, and R. Godin, “An Auto-Associative Neural Network for Information Retrieval,” in The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006, pp. 3492-3498.
  • [3] B. Bratina, N. Muškinja, and B. Tovornik, “Design of an auto-associative neural network by using design of experiments approach,” Neural Computing and Applications, vol. 19, 2010, pp. 207-218.
  • [4] B. J. Fernandes, G. D. Cavalcanti, and T. I. Ren, “Constructive Autoassociative Neural Network for Facial Recognition,” PloS one, vol. 9, 2014, p. e115967.
  • [5] P.-J. Wang and C. Cox, “Study on the application of auto-associative neural network,” in Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on, 2004, pp. 3291-3295.
  • [6] J. L. Galotto, J. O. P. Pinto, L. C. Leite, L. E. B. d. Silva, and B. K. Bose, “Evaluation of the Auto-Associative Neural Network Based Sensor Compensation in Drive Systems,” in 2008 IEEE Industry Applications Society Annual Meeting, 2008, pp. 1-6.
  • [7] M. R. Othman, Z. Zhang, T. Imamura, and T. Miyake, “Modeling driver operation behavior by linear prediction analysis and auto associative neural network,” in Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on, 2009, pp. 649-653.
  • [8] S. Şeker, E. Önal, T. Kaynaş, and T. Ç. Akıncı, “A Neuro Detector Based on the Cybernetic Concepts for Fault Detection in Electric Motors,” 2011.
  • [9] D. Bayram and S. Seker, “Wavelet based neuro-detector for low frequencies of vibration signals in electric motors,” Applied Soft Computing Journal, vol. 13, 2013, pp. 2683-2691.
  • [10] E. Ayaz, M. Uçar, S. Şeker, and B. R. Upadhyaya, “Neuro-detector based on coherence analysis for stator insulation in electric motors,” Electric Power Components and Systems, vol. 37, 2009, pp. 533-546.
  • [11] S. Seker and A. H. Kayran, “Neural network application for fault detection in electric motors,” in 2009 Australasian Universities Power Engineering Conference, 2009, pp. 1-4.
  • [12] D. Dutta Majumder, "Cybernetics and general systems—a unitary science?," Kybernetes, vol. 8, 1979, pp. 7-15.

AN ARTIFICIAL NEURO DETECTOR AND ITS COGNITIVE INTERPRETATION FOR ENGINEERING SYSTEMS

Year 2018, Volume: 3 Issue: 1, 5 - 8, 01.12.2018

Abstract

In this paper the definition for an artificial Neuro-Detector and its
working principles are given conceptually. The methodology to be followed is
simply introduced. Then some examples and suggestions to employ Neuro-detection
in industry are presented through to the real world problems. The cognition run
through a Neuro-Detector is discussed in terms of defining its cognitive
abilities. Then the analogies between a cognitive system and an Artificial
Neural Network based detector system are unfolded.

References

  • [1] M. A. Kramer, “Autoassociative neural networks,” Computers & Chemical Engineering, vol. 16, 1992, pp. 313-328.
  • [2] G. Desjardins, R. Proulx, and R. Godin, “An Auto-Associative Neural Network for Information Retrieval,” in The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006, pp. 3492-3498.
  • [3] B. Bratina, N. Muškinja, and B. Tovornik, “Design of an auto-associative neural network by using design of experiments approach,” Neural Computing and Applications, vol. 19, 2010, pp. 207-218.
  • [4] B. J. Fernandes, G. D. Cavalcanti, and T. I. Ren, “Constructive Autoassociative Neural Network for Facial Recognition,” PloS one, vol. 9, 2014, p. e115967.
  • [5] P.-J. Wang and C. Cox, “Study on the application of auto-associative neural network,” in Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on, 2004, pp. 3291-3295.
  • [6] J. L. Galotto, J. O. P. Pinto, L. C. Leite, L. E. B. d. Silva, and B. K. Bose, “Evaluation of the Auto-Associative Neural Network Based Sensor Compensation in Drive Systems,” in 2008 IEEE Industry Applications Society Annual Meeting, 2008, pp. 1-6.
  • [7] M. R. Othman, Z. Zhang, T. Imamura, and T. Miyake, “Modeling driver operation behavior by linear prediction analysis and auto associative neural network,” in Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on, 2009, pp. 649-653.
  • [8] S. Şeker, E. Önal, T. Kaynaş, and T. Ç. Akıncı, “A Neuro Detector Based on the Cybernetic Concepts for Fault Detection in Electric Motors,” 2011.
  • [9] D. Bayram and S. Seker, “Wavelet based neuro-detector for low frequencies of vibration signals in electric motors,” Applied Soft Computing Journal, vol. 13, 2013, pp. 2683-2691.
  • [10] E. Ayaz, M. Uçar, S. Şeker, and B. R. Upadhyaya, “Neuro-detector based on coherence analysis for stator insulation in electric motors,” Electric Power Components and Systems, vol. 37, 2009, pp. 533-546.
  • [11] S. Seker and A. H. Kayran, “Neural network application for fault detection in electric motors,” in 2009 Australasian Universities Power Engineering Conference, 2009, pp. 1-4.
  • [12] D. Dutta Majumder, "Cybernetics and general systems—a unitary science?," Kybernetes, vol. 8, 1979, pp. 7-15.
There are 12 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Duygu Bayram Kara 0000-0001-8184-8510

Serhat Seker 0000-0001-5816-2211

Publication Date December 1, 2018
Published in Issue Year 2018 Volume: 3 Issue: 1

Cite

APA Bayram Kara, D., & Seker, S. (2018). AN ARTIFICIAL NEURO DETECTOR AND ITS COGNITIVE INTERPRETATION FOR ENGINEERING SYSTEMS. The Journal of Cognitive Systems, 3(1), 5-8.