Treatment of L-Fuzzy contexts with absent values

  • Authors:
  • C. Alcalde;A. Burusco;R. Fuentes-González;I. Zubia

  • Affiliations:
  • Escuela Universitaria Politécnica, Departamento de Matemática Aplicada, Universidad del País Vasco, Plaza de Europa 1, 20018 San Sebastián, Spain;Departamento de Automática y Computación, Universidad Pública de Navarra, Campus de Arrosadía, 31006 Pamplona, Spain;Departamento de Automática y Computación, Universidad Pública de Navarra, Campus de Arrosadía, 31006 Pamplona, Spain;Escuela Universitaria Politécnica, Departamento de Ingeniería Eléctrica, Universidad del País Vasco, Plaza de Europa 1, 20018 San Sebastián, Spain

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2009

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Abstract

This work shows how to extract the missing information from an interval-valued L-Fuzzy context with some unknown values. Absent values are replaced using implications between attributes with high levels of support and confidence. Three kinds of implications are defined and analyzed for this purpose. We apply these results to an electrical network simulation, where the estimated relations between faulty power lines and voltage measurements can be compared with their real values.