AYUDA A LA DECISION CON INFORMACION DIFUSA Y CRITERIOS MULTIPLES. APLICACION A LA GESTION DE DESASTRES

TIN2012-32482

Nombre agencia financiadora Ministerio de Economía y Competitividad
Acrónimo agencia financiadora MINECO
Programa Programa Nacional de Investigación Fundamental
Subprograma Investigación fundamental no-orientada
Convocatoria Proyectos de Investigación Fundamental No-Orientada
Año convocatoria 2012
Unidad de gestión Dirección General de Investigación Científica y Técnica
Centro beneficiario UNIVERSIDAD COMPLUTENSE DE MADRID
Centro realización FACULTAD DE CIENCIAS MATEMÁTICAS - DEPARTAMENTO DE ESTADÍSTICA E INVESTIGACIÓN OPERATIVA
Identificador persistente http://dx.doi.org/10.13039/501100003329

Publicaciones

Resultados totales (Incluyendo duplicados): 3
Encontrada(s) 1 página(s)

Type-2 fuzzy entropy-sets

Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
  • Miguel Turullols, Laura de
  • Santos, Helida
  • Sesma Sara, Mikel
  • Bedregal, Benjamin
  • Jurío Munárriz, Aránzazu
  • Bustince Sola, Humberto
The final goal of this study is to adapt the concept
of fuzzy entropy of De Luca and Termini to deal with Type-2
Fuzzy Sets. We denote this concept Type-2 Fuzzy Entropy-Set.
However, the construction of the notion of entropy measure on
an infinite set, such us [0, 1], is not effortless. For this reason,
we first introduce the concept of quasi-entropy of a Fuzzy Set
on the universe [0, 1]. Furthermore, whenever the membership
function of the considered Fuzzy Set in the universe [0, 1] is
continuous, we prove that the quasi-entropy of that set is a fuzzy
entropy in the sense of De Luca y Termini. Finally, we present
an illustrative example where we use Type-2 Fuzzy Entropy-Sets
instead of fuzzy entropies in a classical fuzzy algorithm., This work was supported by the Research Service of Universidad Publica
de Navarra as well as by the projects TIN2013-40765-P and TIN2012-32482 of
the Spanish Ministry of Science and by the Brazilian funding agencies CNPq
(under Proc. No. 480832/2011-0 and No. 307681/2012-2) and CAPES (under
Proc. No. 5778/2014-00).




A historical account of types of fuzzy sets and their relationships

Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
  • Bustince Sola, Humberto
  • Barrenechea Tartas, Edurne
  • Pagola Barrio, Miguel
  • Fernández Fernández, Francisco Javier
  • Xu, Zeshui
  • Bedregal, Benjamin
  • Montero, Javier
  • Hagras, Hani
  • Herrera, Francisco
  • Baets, Bernard de
In this work we review the definition and basic
properties of the different types of fuzzy sets that have appeared
up to now in the literature. We also analyze the relationships
between them and enumerate some of the applications in which
they have been used., This work was supported by projects TIN2013-40765-P and TIN2012-32482 of the Spanish Ministry of Science and by the Brazilian funding agency CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnologico), under Proc. Nos. 480832/2011-0 and 307681/2012-2




Design of maintenance structures for rural electrification with solar home systems. The case of the Moroccan program

Archivo Digital UPM
  • Carrasco Moreno, Luis Miguel
  • Martín Campos, F.J.
  • Narvarte Fernández, Luis
  • Ortuño, M.T.
  • Vitoriano, B.
In decentralised rural electrification through solar home systems, private companies and promoting institutions are faced with the problem of deploying maintenance structures to operate and guarantee the service of the solar systems for long periods (ten years or more). The problems linked to decentralisation, such as the dispersion of dwellings, difficult access and maintenance needs, makes it an arduous task. This paper proposes an innovative design tool created ad hoc for photovoltaic rural electrification based on a real photovoltaic rural electrification program in Morocco as a special case study. The tool is developed from a mathematical model comprising a set of decision variables (location, transport, etc.) that must meet certain constraints and whose optimisation criterion is the minimum cost of the operation and maintenance activity assuming an established quality of service. The main output of the model is the overall cost of the maintenance structure. The best location for the local maintenance headquarters and warehouses in a given region is established, as are the number of maintenance technicians and vehicles required.