Type-(2,k) overlap indices

Identificadores
URI: https://hdl.handle.net/10481/109601
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Autor
Roldán López de Hierro, Antonio Francisco; Roldán, Concepción; Tíscar, Miguel Ángel; Takac, Zdenko; Santiago, Regivan H.N.; Dimuro, Graçaliz P.; Fernández, Javier; Bustince, Humberto
Editorial
IEEE-Inst Electrical Electronics Engineers Inc.
Materia
Overlap function
 
Overlap index
 
Type-2 fuzzy set
 
Función de solapamiento
 
Índice de solapamiento
 
Conjunto difuso
 
Conjunto difuso de tipo 2
 
Fecha
2023-03
Referencia bibliográfica
A. F. Roldán López de Hierro, C. Roldán, M. Á. Tíscar, Z. Takac, R. H. N. Santiago, G. P. Dimuro, J. Fernández, H. Bustince (2023). Type-(2,k) overlap indices, IEEE Trans. Fuzzy Syst., vol. 31, no. 3, pp. 860-874
Patrocinador
Junta de Andalucía, Project A-FQM-170-UGR20 (Program FEDER Andalucía 2014-2020); Junta de Andalucía, Project FQM-365 (Andalusian CICYE); Ministerio de Ciencia e Innovación, Project PID2020-119478GB-I00; Ministerio de Ciencia e Innovación, Project PID2019-108392GB-I00 (AEI/10.13039/501100011033); CNPq under Grant 301618/2019-4; FAPERGS under Grant 19/2551-0001660; VEGA under Grant 1/0267/21
Resumen
Automatic image detection is one of the most important areas in computing due to its potential application in numerous real-world scenarios. One important tool to deal with that is called overlap indices. They were introduced as a procedure to provide the maximum lack of knowledge when comparing two fuzzy objects. They have been successfully applied in the following fields: image processing, fuzzy rule-based systems, decision making, and computational brain interfaces. This notion of overlap indices is also necessary for applications in which type-2 fuzzy sets are required. In this article, we introduce the notion of type-(2,k) overlap index (k in {0, 1, 2}) in the setting of type-2 fuzzy sets. We describe both the reasons that have led to this notion and the relationships that naturally arise among the algebraic underlying structures. Finally, we illustrate how type-(2,k) overlap indices can be employed in the setting of fuzzy rule-based systems when the involved objects are type-2 fuzzy sets.
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