Exploració per tema "Fuzzy inductive reasoning"

Ara es mostren els items 11-18 de 18

    • Hybrid evolutionary data analysis technique for environmental modeling 

      Acosta, Jesus; Nebot Castells, M. Àngela; Fuertes Armengol, José Mª (International Centre for Numerical Methods in Engineering (CIMNE), 2006)
      Text en actes de congrés
      Accés obert
      In this work an evolutionary fuzzy system (EFS) is presented and applied to an environmental problem, i.e. modeling ozone concentrations. The hybrid system is composed by a FIR methodology and a genetic algorithm (GA) that ...

    • Hybrid methodologies for electricity load forecasting: Entropy-based feature selection with machine learning and soft computing techniques 

      Jurado Gómez, Sergio; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Avellana, Narcís (2015-06-15)
      Article
      Accés obert
      Scientific community is currently doing a great effort of research in the area of Smart Grids because energy production, distribution, and consumption play a critical role in the sustainability of the planet. The main ...

    • K nearest neighbour optimal selection in fuzzy inductive reasoning for smart grid applications 

      Jurado Gómez, Sergio; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (Institute of Electrical and Electronics Engineers (IEEE), 2019)
      Text en actes de congrés
      Accés obert
      Energy recasting has been an area of great interest in the last years. It unlocks, not only the Smart Grid's potential with load balancing but also new business models and added value services. To achieve an accurate, ...

    • Método multiobjetivo de aprendizaje para razonamiento inductivo difuso 

      Acosta, Jesús; Nebot Castells, M. Àngela; Fuertes Armengol, José Mª (2006-10)
      Report de recerca
      Accés obert
      It has been recognized in various studies that the variations in the granularity (number of classes per variable) and the membership functions have a significant effect in the behaviour of the fuzzy systems. The FIR ...

    • Modeling the control of the central nervous system over the cardiovascular system using support vector machines 

      Díaz, José; Acosta, Jesús; González, Rafael; Cota, Juan; Sifuentes, Ernesto; Nebot Castells, M. Àngela (Elsevier, 2018-02-01)
      Article
      Accés obert
      The control of the central nervous system (CNS) over the cardiovascular system (CS) has been modeled using different techniques, such as fuzzy inductive reasoning, genetic fuzzy systems, neural networks, and nonlinear ...

    • PEM fuel cell fault diagnosis via a hybrid methodology based on fuzzy and pattern recognition techniques 

      Escobet Canal, Antoni; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (2014-08)
      Article
      Accés obert
      In this work, a fault diagnosis methodology termed VisualBlock-Fuzzy Inductive Reasoning, i.e. VisualBlock-FIR, based on fuzzy and pattern recognition approaches is presented and applied to PEM fuel cell power systems. The ...

    • Rule-based assistance to brain tumour diagnosis using LR-FIR 

      Nebot Castells, M. Àngela; Castro Espinoza, Félix Agustín; Vellido Alcacena, Alfredo; Julià Sapé, Margarida; Arús, Carles (2008-09)
      Article
      Accés restringit per política de l'editorial
      This paper describes a process of rule-extraction from a multi-centre brain tumour database consisting of nuclear magnetic res- onance spectroscopic signals. The expert diagnosis of human brain tumours can benefit from ...

    • Wrapper-based fuzzy inductive reasoning model identification for imbalance data classification 

      Bagherpour, Solmaz; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (Institute of Electrical and Electronics Engineers (IEEE), 2018)
      Comunicació de congrés
      Accés obert
      Fuzzy Inductive Reasoning (FIR) is a qualitative inductive modeling and simulation methodology for dealing with complex dynamical systems. FIR has proven to be a powerful tool for qualitative model identification and ...