dc.creator | Peng, Hong | es |
dc.creator | Wang, Jun | es |
dc.creator | Pérez Jiménez, Mario de Jesús | es |
dc.creator | Wang, Hao | es |
dc.creator | Shao, Jie | es |
dc.creator | Wang, Tao | es |
dc.date.accessioned | 2018-10-31T11:18:43Z | |
dc.date.available | 2018-10-31T11:18:43Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Peng, H., Wang, J., Pérez Jiménez, M.d.J., Wang, H., Shao, J. y Wang, T. (2013). Fuzzy reasoning spiking neural P system for fault diagnosis. Information Sciences, 235 (junio 2013), 106-116. | |
dc.identifier.issn | 0020-0255 | es |
dc.identifier.uri | https://hdl.handle.net/11441/79742 | |
dc.description.abstract | 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. | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación TIN2009–13192 | es |
dc.description.sponsorship | Junta de Andalucía P08-TIC-04200 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Information Sciences, 235 (junio 2013), 106-116. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Fault diagnosis | es |
dc.subject | P systems | es |
dc.subject | Spiking Neural P systems | es |
dc.subject | Fuzzy knowledge representation | es |
dc.subject | Fuzzy reasoning | es |
dc.title | Fuzzy reasoning spiking neural P system for fault diagnosis | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.projectID | TIN2009–13192 | es |
dc.relation.projectID | P08-TIC-04200 | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0020025512004793 | es |
dc.identifier.doi | 10.1016/j.ins.2012.07.015 | es |
dc.contributor.group | Universidad de Sevilla. TIC193: Computación Natural | es |
idus.format.extent | 11 | es |
dc.journaltitle | Information Sciences | es |
dc.publication.volumen | 235 | es |
dc.publication.issue | junio 2013 | es |
dc.publication.initialPage | 106 | es |
dc.publication.endPage | 116 | es |
dc.identifier.sisius | 20366582 | es |
dc.contributor.funder | Ministerio de Ciencia e Innovación (MICIN). España | |
dc.contributor.funder | Junta de Andalucía | |