Fuzzy dissimilarities and the fuzzy choquet integral of triangular fuzzy numbers on [0,1]

Having in mind the huge amount of data daily registered in the world, it is becoming increasingly important to summarize the information included in a data set. In Statistics and Computer Science, this task is successfully carried out by aggregation functions. One of the most widely applied methodol...

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Detalles Bibliográficos
Autores: Roldán López de Hierro, Antonio Francisco, Cruz, Anderson, Santiago, Regivan, Roldán, Concepción, García-Zamora, Diego, Neres, Fernando, Bustince Sola, Humberto
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2025
País:España
Institución:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/53590
Acceso en línea:https://hdl.handle.net/2454/53590
Access Level:acceso embargado
Palabra clave:Alpha-ordering
Binary relation
Choquet integral
Dissimilarity
Fuzzy number
Ranking
Descripción
Sumario:Having in mind the huge amount of data daily registered in the world, it is becoming increasingly important to summarize the information included in a data set. In Statistics and Computer Science, this task is successfully carried out by aggregation functions. One of the most widely applied methodologies of aggregating data is the Choquet integral. The main aim of this paper is to introduce an appropriate notion of Choquet integral in the context of fuzzy numbers. To do this, we face three challenges: the underlying uncertainty when handling fuzzy numbers, the way to order fuzzy numbers by appropriate binary relations and the way to compute the dissimilarity among fuzzy numbers. Illustrative examples are given by involving the α-order on the family of all triangular fuzzy numbers with support on [0,1].