Enviaments recents

  • Comparison of Methods to Predict Ozone Concentration 

    Orozco Luquero, Jorge (2004-01)
    Report de recerca
    Accés obert
    Several methods have been applied to the prediction of ozone concentration. In this work, an Heterogeneous Neural Network (HNN) is used to perform the same task. Different capabilities of HNN are exploited like imprecision ...
  • Detecció i identificació de falles en una xarxa de distribució d'aigües 

    Escobet Canal, Antoni; Nebot Castells, M. Àngela (2001-04)
    Report de recerca
    Accés obert
    This technical report deals with two of the main tasks of Fault Monitoring Systems (FMS): fault detection and fault identification. During fault detection, the FMS should recognize that the plant behavior is abnormal, ...
  • Aplicación de algoritmos de clustering desarrollados en el entorno FIR a la predicción de la concentración de ozono 

    Gómez Miranda, Pilar; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (2002-06-06)
    Report de recerca
    Accés obert
    El presente trabajo tiene como objetivo estudiar la aplicación de diferentes al-goritmos de clustering desarrollados en el entorno de la metodología FIR al problema de la predicción a largo plazo de las concentraciones ...
  • Automatic construction of rules fuzzy for modelling and prediction of the central nervous system 

    Múgica Álvarez, Francisco; Nebot Castells, M. Àngela; Gómez Miranda, Pilar (2002-07-03)
    Report de recerca
    Accés obert
    The main goal of this work is to study the performance of CARFIR (Automatic Construction of Rules in Fuzzy Inductive Reasoning) methodology for the modelling and prediction of the human central nervous system (CNS). The ...
  • Feature selection algorithms: a survey and experimental evaluation 

    Molina, Luis; Belanche Muñoz, Luis Antonio; Nebot Castells, M. Àngela (2003-02)
    Report de recerca
    Accés obert
    In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certain situations. This work reviews several ...
  • Evolutionary optimization of heterogeneous problems 

    Belanche Muñoz, Luis Antonio (2003-02)
    Report de recerca
    Accés obert
    A large number of practical optimization problems involve elements of quite diverse nature, described as mixtures of qualitative and quantitative information, and whose description is possibly incomplete. In this work we ...
  • Incremental construction of LSTM recurrent neural network 

    Ribeiro, Evandsa Sabrine Lopes-Lima; Alquézar Mancho, René (2002-12)
    Report de recerca
    Accés obert
    Long Short--Term Memory (LSTM) is a recurrent neural network that uses structures called memory blocks to allow the net remember significant events distant in the past input sequence in order to solve long time lag ...
  • Margin maximization with feed-forward neural networks: a comparative study with support vector machines and AdaBoost 

    Romero Merino, Enrique; Màrquez Villodre, Lluís; Carreras Pérez, Xavier (2003-06)
    Report de recerca
    Accés obert
    Feed-forward Neural Networks (FNN) and Support Vector Machines (SVM) are two machine learning frameworks developed from very different starting points of view. In this work a new learning model for FNN is proposed such ...
  • Exploiting diversity of margin-based classifiers 

    Romero Merino, Enrique; Carreras Pérez, Xavier; Màrquez Villodre, Lluís (2003-12)
    Report de recerca
    Accés obert
    An experimental comparison among Support Vector Machines, AdaBoost and a recently proposed model for maximizing the margin with Feed-forward Neural Networks has been made on a real-world classification problem, namely ...
  • Feature selection for microarray gene expression data using simulated annealing guided by the multivariate joint entropy 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (2013)
    Report de recerca
    Accés obert
    In this work a new way to calculate the multivariate joint entropy is presented. This measure is the basis for a fast information-theoretic based evaluation of gene relevance in a Microarray Gene Expression data context. ...

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