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A New Interval Arithmetic-Based Neural Network

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Issues in the Use of Neural Networks in Information Retrieval

Part of the book series: Studies in Computational Intelligence ((SCI,volume 661))

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Abstract

The aim of this chapter is to design a new model of fuzzy nonlinear perceptron, based on alpha level sets. The new model entitled Fuzzy Nonlinear Perceptron based on Alpha Level Sets (FNPALS) Iatan, Neuro-fuzzy system for pattern recognition (in Romanian), PhD thesis, 2003, [1], Iatan and de Rijke, A new interval arithmetic based neural network, 2014, [2] differs from the other fuzzy variants of the nonlinear perceptron, where the fuzzy numbers are represented by membership values. In the case of FNPALS, the fuzzy numbers are represented through the alpha level sets.

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Notes

  1. 1.

    Leondes, C. T., Fuzzy Logic and Expert Systems Applications. San Diego, Academic Press, 1998.

References

  1. I. Iatan. Neuro-Fuzzy Systems for Pattern Recognition (in Romanian). PhD thesis, Faculty of Electronics, Telecommunications and Information Technology- University Politehnica of Bucharest, PhD supervisor: Prof. dr. Victor Neagoe, 2003.

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  2. I. Iatan and M. de Rijke. A new interval arithmetic based neural network. (work in progress), 2014.

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  3. A. Muñoz San Roque, C. Maté, J. Arroyo, and A. Sarabia. iMLP: Applying multi-layer perceptrons to interval-valued data. Neural Processing Letters, 25:157–169, 2007.

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  4. C. T. Leondes. Fuzzy Logic and Expert Systems Applications. San Diego, Academic Press, 1998.

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  5. M. Umano and Y. Ezawa. Execution of approximate reasoning by neural network. In Proceedings of FAN Symposium, pages 267–273, 1991.

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  6. K. Uehara and M. Fujise. Learning of fuzzy inference criteria with artificial neural network. In Proc. 1st Int. Conf. on Fuzzy Logic and Neural Networks, pages 193–198, 1990.

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Authors and Affiliations

  1. Department of Mathematics and Computer Sciences, Technical University of Civil Engineering, Bucharest, Romania

    Iuliana F. Iatan

Authors
  1. Iuliana F. Iatan
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Correspondence to Iuliana F. Iatan .

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Iatan, I.F. (2017). A New Interval Arithmetic-Based Neural Network. In: Issues in the Use of Neural Networks in Information Retrieval. Studies in Computational Intelligence, vol 661. Springer, Cham. https://doi.org/10.1007/978-3-319-43871-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-43871-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43870-2

  • Online ISBN: 978-3-319-43871-9

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