%0 Generic %D 2015 %T Computational efficiency of P systems with symport/antiport rules and membrane separation %A Luis Valencia-Cabrera %A Bosheng Song %A Luis F. Macías-Ramos %A Linqiang Pan %A Agustín Riscos-Núñez %A Mario J. Pérez-Jiménez %C Sevilla, España %I Fénix Editora %P 325-370 %S Proceedings of the Thirteenth Brainstorming Week on Membrane Computing, %U http://www.cs.us.es/~marper/investigacion/proceedings-13th-BWMC.pdf %V 1 %X Spiking neural P systems (SN P systems) have been well established as a novel class of distributed parallel computing models. Some features that SN P systems possess are attractive to fault diagnosis. However, handling fuzzy diagnosis knowledge and reasoning is required for many fault diagnosis applications. The lack of ability is a major problem of existing SN P systems when applying them to the fault diagnosis domain. Thus, we extend SN P systems by introducing some new ingredients (such as three types of neurons, fuzzy logic and new firing mechanism) and propose the fuzzy reasoning spiking neural P systems (FRSN P systems). The FRSN P systems are particularly suitable to model fuzzy production rules in a fuzzy diagnosis knowledge base and their reasoning process. Moreover, a parallel fuzzy reasoning algorithm based on FRSN P systems is developed according to neuron’s dynamic firing mechanism. Besides, a practical example of transformer fault diagnosis is used to demonstrate the feasibility and effectiveness of the proposed FRSN P systems in fault diagnosis problem. %8 02/2015