• A genetic programming approach for economic forecasting with survey expectations 

      Claveria González, Oscar; Monte Moreno, Enrique; Torra Porras, Salvador (Multidisciplinary Digital Publishing Institute, 2022-06-30)
      Article
      Accés obert
      We apply a soft computing method to generate country-specific economic sentiment indicators that provide estimates of year-on-year GDP growth rates for 19 European economies. First, genetic programming is used to evolve ...
    • A hierarchical perspective to fuzzy inductive reasoning: an attempt to obtain more understandable fuzzy inductive reasoning rules 

      Bagherpour, Solmaz; Múgica Álvarez, Francisco; Nebot Castells, M. Àngela (2015)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      Generalizing hypotheses based on the past data in order to predict the future is the essential core of human learning. Various successful methods and techniques have been developed so far that perform some sort of ...
    • A soft computing decision support framework to improve the e-learning experience 

      Castro Espinoza, Félix Agustín; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (Society for Computer Simulation International San Diego, 2008)
      Text en actes de congrés
      Accés obert
      In this paper an e-learning decision support framework based on a set of soft computing techniques is presented. The framework is mainly based on the FIR methodology and two of its key extensions: a set of Causal Relevance ...
    • Fuzzy inductive reasoning forecasting strategies able to cope with missing data: A smart grid application 

      Jurado Gómez, Sergio; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Mihaylov, Mihail (2017-02)
      Article
      Accés obert
      Dealing with missing data is of great practical and theoretical interest in forecasting applications. In this study, we deal with the problem of forecasting with missing data in smart grid and BEMS applications, where the ...
    • Fuzzy inductive reasoning forecasting strategies able to cope withmissing data: A smart grid application 

      Jurado, Sergio; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Mihaylov, Mihail (2017-02)
      Article
      Accés obert
      Dealing with missing data is of great practical and theoretical interest in forecasting applications. In this study, we deal with the problem of forecasting with missing data in smart grid and BEMS applications, where the ...
    • Fuzzy inductive reasoning: a consolidated approach to data-driven construction of complex dynamical systems 

      Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (2012)
      Article
      Accés restringit per política de l'editorial
      Fuzzy inductive reasoning (FIR) is a modelling and simulation methodology derived from the General Systems Problem Solver. It compares favourably with other soft computing methodologies, such as neural networks, genetic ...
    • 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, ...
    • Random-Walk laplacian for frequency analysis in periodic graphs 

      Boukrab, Rachid; Pagès Zamora, Alba Maria (Multidisciplinary Digital Publishing Institute (MDPI), 2021-02-11)
      Article
      Accés obert
      This paper presents the benefits of using the random-walk normalized Laplacian matrix as a graph-shift operator and defines the frequencies of a graph by the eigenvalues of this matrix. A criterion to order these frequencies ...
    • Researching of the deep neural network for amber gemstone classification 

      Castro Rios, Ramiro Saito (Universitat Politècnica de Catalunya, 2018)
      Projecte Final de Màster Oficial
      Accés obert
      Realitzat a/amb:   Kauno Technologijos universitetas
      This project is based on the researching of the deep neural network for the classification of amber gemstone seen as a great opportunity to expand the range of application of the well known deep learning, which have been ...