Now showing items 1-6 of 6

    • Application of multi-objective genetic algorithms to fitting piecewise linear models 

      Gascón González, Alberto; Sánchez Ubeda, Eugenio Francisco (Universidad de La Laguna y Asociación Española de Inteligencia Artificial (AEPIA) (Tenerife, España), 07/11/2011)
      Despite the conflicting nature of low-complexity models versus error minimization in machine learning problems, the application of multi-objective learning algorithms is only recently acquiring an evident importance. In ...
    • Automatic specification of piecewise linear additive models: application to forecasting natural gas demand 

      Gascón González, Alberto; Sánchez Ubeda, Eugenio Francisco (01/01/2018)
      When facing any forecasting problem not only is accuracy on the predictions sought. Also, useful information about the underlying physics of the process and about the relevance of the forecasting variables is very much ...
    • Estadística II 

      Gascón González, Alberto; Sánchez Úbeda, Eugenio Francisco (29/08/2019)
    • Estadística II 

      Gascón González, Alberto; Sánchez Úbeda, Eugenio Francisco (20/07/2020)
    • Genetic algorithms and mathematical programming to crack the spanish strip cipher 

      Campos Fernández, Francisco Alberto; Gascón González, Alberto; Latorre Canteli, Jesús María; Soler Fuensanta, J. Ramón (13/01/2013)
      This article describes the application of modern algorithms to crack the official encryption method of the Spanish Civil War: the Strip Cipher. It shows the differences in efficiency and effectiveness between a genetic ...
    • The Thor model: an automatic nonlinear additive model for time series 

      Gascón González, Alberto; Sánchez Ubeda, Eugenio Francisco
      When facing an unknown forecasting problem, accuracy on the predictions as well as useful information about the underlying physics of the process are mostly appreciated. In this paper the Thor model, a fully interpretable ...