Application of Fuzzy Reasoning Spiking Neural P Systems to Fault Diagnosis

Tao Wang, Gexiang Zhang, Haina Rong, Mario J. Pérez-Jiménez

Abstract


This paper discusses the application of fuzzy reasoning spiking neural P systems with trapezoidal fuzzy numbers (tFRSN P systems) to fault diagnosis of power systems, where a matrix-based fuzzy reasoning algorithm based on the dynamic firing mechanism of neurons is used to develop the inference ability of tFRSN P systems from classical reasoning to fuzzy reasoning. Some case studies show the effectiveness of the presented method. We also briefly draw comparisons between the presented method and several main fault diagnosis approaches from the perspectives of knowledge representation and inference process.


Keywords


fuzzy reasoning spiking neural P system with trapezoidal fuzzy number, fuzzy reasoning, fault diagnosis, trapezoidal fuzzy number, linguistic term

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References


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DOI: https://doi.org/10.15837/ijccc.2014.6.1485



Copyright (c) 2017 Tao Wang, Gexiang Zhang, Haina Rong, Mario J. Pérez-Jiménez

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