f-HybridMem: a consensual analysis via fuzzy consensus measures and penalty functions

Oliveira, Lizandro de Souza; Yamin, Adenauer; Reiser, Renata; Santos, Helida

Publication:
f-HybridMem: a consensual analysis via fuzzy consensus measures and penalty functions

dc.contributor.author	Oliveira, Lizandro de Souza
dc.contributor.author	Yamin, Adenauer
dc.contributor.author	Reiser, Renata
dc.contributor.author	Santos, Helida
dc.contributor.department	Estadística, Informática y Matemáticas	es_ES
dc.contributor.department	Estatistika, Informatika eta Matematika	eu
dc.date.accessioned	2023-03-03T12:24:19Z
dc.date.available	2023-03-03T12:24:19Z
dc.date.issued	2022
dc.date.updated	2023-03-03T09:54:26Z
dc.description.abstract	This paper considers the consensual analysis in decision-making (CDM) processes based on fuzzy logic (FL) and interval-valued fuzzy logic (IVFL), providing a CDM-strategy, by exploring the axiomatic properties of fuzzy consensus measures (FCM) via penalty functions. Thus, two models are formalized, FS-FCM and IVFS-FCM. In the former, the fuzzy-valued lattice enables the analysis of fuzzy information for linguistic variables (LV), which is obtained by the aggregation of penalty functions. And, in the latter, the consensus measures of fuzzy sets are aggregated to build a new consensual analysis modeling. Thus, e.g., the cohesion of several terms related to the same LV can be analyzed, and also the coherence between fuzzy sets referring to the lowest and highest projections. Such models decide based on relevance criteria and qualitative assessments, via the selection of alternatives, supporting the corresponding algorithmic strategies: FS-FCM strategy, applied to fuzzy values, and IVFS-FCM strategy, covering fuzzy sets. The Intf-HybridMem approach explores the access patterns to volatile and non-volatile memories related to decision-making in two steps: (i) the FS-FCM strategy explores consensus measures of fuzzy values from membership functions; and (ii) the IVFS-FCM strategy, modeling inaccuracy inherent in input variables, as read/write frequency and access recency, also including the migration recommendation as output, which is validated by evaluations carried out in both proposed strategies.	en
dc.description.sponsorship	This work was partially supported by CAPES, PQ/CNPq (309160/2019-7), PqG/FAPERGS (21/2551-0002057-1) and FAPERGS/CNPq PRONEX (16/2551-0000488-9).	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Souza Oliveira, L. D., Correa Yamin, A., Sander Reiser, R. H., & Salles Santos, H. (2022). F-hybridmem: A consensual analysis via fuzzy consensus measures and penalty functions. 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8. https://doi.org/10.1109/FUZZ-IEEE55066.2022.9882879	en
dc.identifier.doi	10.1109/FUZZ-IEEE55066.2022.9882879
dc.identifier.isbn	978-1-6654-6710-0
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/44831
dc.language.iso	eng	en
dc.publisher	IEEE	en
dc.relation.ispartof	IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) 2022 p.1-8	en
dc.relation.publisherversion	https://doi.org/10.1109/FUZZ-IEEE55066.2022.9882879
dc.rights	© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work	en
dc.rights.accessRights	Acceso abierto / Sarbide irekia	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	en
dc.subject	Decision Making Problem	en
dc.subject	Fuzzy Consensus Measure	en
dc.subject	Hybrid Memory Management	en
dc.subject	Penalty Functions	en
dc.title	f-HybridMem: a consensual analysis via fuzzy consensus measures and penalty functions	en
dc.type	Contribución a congreso / Biltzarrerako ekarpena	es
dc.type	info:eu-repo/semantics/conferenceObject	en
dc.type.version	Versión aceptada / Onetsi den bertsioa	es
dc.type.version	info:eu-repo/semantics/acceptedVersion	en
dspace.entity.type	Publication