Recent Submissions

  • 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)
    Conference report
    Open Access
    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, ...
  • Charting perceptual spaces with fuzzy rules 

    Paz Ortiz, Alejandro Iván; Nebot Castells, M. Àngela; Romero Merino, Enrique; Múgica Álvarez, Francisco (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Conference lecture
    Open Access
    Algorithmic music nowadays performs domain specific tasks for which classical algorithms do not offer optimal solutions or require user's expertise. Among these tasks is the extraction of models from data that offer an ...
  • Comparison between composite index solution surfaces with fuzzy composite index decision surfaces 

    González Cárdenas, Rubén; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Conference lecture
    Open Access
    Composite indices are used in many of the traditional approaches to measure risk to natural hazards. However, such indices are often built assuming linear interdependencies between the aggregated components, comprising in ...
  • Enhanced equal frequency partition method for the identification of a water demand system 

    Escobet Canal, Antoni; Huber Garrido, Rafael M.; Nebot Castells, M. Àngela; Cellier, François E. (Sarjoughian,H.S.; Cellier, F.E.; Marefat, M.M.; Rozenblit, J.W. (eds.) Institute of Electrical and Electronics Engineers, 2000)
    Conference report
    Open Access
    This paper deals with unsupervised partitioning. A first goal of this paper is to present an enhancement to the Equal Frequency Partition (EFP) method that allows to reduce, to some extent, the main drawback of this classical ...
  • 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)
    Conference report
    Open Access
    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 ...
  • 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)
    Conference lecture
    Open Access
    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 ...
  • Bridging deep and kernel methods 

    Belanche Muñoz, Luis Antonio; Ruiz Costa-Jussà, Marta (2017)
    Conference report
    Restricted access - publisher's policy
    There has been some exciting major progress in recent years in data analysis methods, including a variety of deep learning architectures, as well as further advances in kernel-based learning methods, which have demonstrated ...
  • Benchmarking the selection of the hidden-layer weights in extreme learning machines 

    Romero Merino, Enrique (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Conference report
    Open Access
    Recent years have seen a growing interest in neural networks whose hidden-layer weights are randomly selected, such as Extreme Learning Machines (ELMs). These models are motivated by their ease of development, high ...
  • A prospective fuzzy approach for the development of integral seismic risk scenarios for Barcelona, Spain 

    González Cárdenas, Rubén; Múgica Álvarez, Francisco; Nebot Castells, M. Àngela (SciTePress, 2017)
    Conference report
    Restricted access - publisher's policy
    We create a set of synthetic seismic risk scenarios by combining stochastic seismic simulations with social fragility indicators by mean of a fuzzy Mamdani type inference nested-model. The original values of the social ...
  • Modeling a flue-gas desulfurization plant with a fuzzy methodology to optimize the SO2 absorption process 

    Escobet Canal, Antoni; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Gamisans Noguera, Javier; Guimerà Villalba, Xavier (2017)
    Conference report
    Restricted access - publisher's policy
  • Bayesian semi non-negative matrix factorisation 

    Vilamala Muñoz, Albert; Vellido Alcacena, Alfredo; Belanche Muñoz, Luis Antonio (I6doc.com, 2016)
    Conference report
    Open Access
    Non-negative Matrix Factorisation (NMF) has become a standard method for source identification when data, sources and mixing coefficients are constrained to be positive-valued. The method has recently been extended to allow ...
  • A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration 

    Paz Ortiz, Iván; Nebot Castells, M. Àngela; Romero Merino, Enrique; Múgica Álvarez, Francisco; Vellido Alcacena, Alfredo (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    Conference lecture
    Open Access
    Algorithmic composition is the process of creating musical material by means of formal methods. As a consequence of its design, algorithmic composition systems are (explicitly or implicitly) described in terms of parameters. ...

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