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Electric Power System Fault Diagnosis with Membrane Systems

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Real-life Applications with Membrane Computing

Part of the book series: Emergence, Complexity and Computation ((ECC,volume 25))

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Abstract

Spiking Neural P systems (SN P systems, for short) are used in electric power systems fault diagnostics, by expanding their modeling capabilities with fuzzy theory concepts. The following variants of SN P systems are introduced and investigated: fuzzy reasoning spiking neural P systems with real numbers, weighted fuzzy reasoning spiking neural P systems and fuzzy reasoning spiking neural P systems with trapezoidal fuzzy numbers.

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Authors and Affiliations

  1. Key Laboratory of Fluid and Power Machinery, Ministry of Education, Xihua University, Chengdu, China

    Gexiang Zhang

  2. Robotics Research Center, Xihua University, Chengdu, China

    Gexiang Zhang

  3. Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla, Spain

    Mario J. Pérez-Jiménez

  4. School of Electrical Engineering and Computer Science, University of Bradford, Bradford, UK

    Marian Gheorghe

Authors
  1. Gexiang Zhang
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  2. Mario J. Pérez-Jiménez
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  3. Marian Gheorghe
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Correspondence to Gexiang Zhang .

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Zhang, G., Pérez-Jiménez, M.J., Gheorghe, M. (2017). Electric Power System Fault Diagnosis with Membrane Systems. In: Real-life Applications with Membrane Computing. Emergence, Complexity and Computation, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-55989-6_5

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  • DOI: https://doi.org/10.1007/978-3-319-55989-6_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55987-2

  • Online ISBN: 978-3-319-55989-6

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