Publicaciones
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Revistas Internacionales
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Herrera, L.J., Pomares, H., Rojas, I., Valenzuela, O., Prieto, A., "TaSe, a Taylor Series Based Fuzzy System Model that Combines Interpretability and Accuracy" Fuzzy Sets and Systems, Elsevier, 153 (2005) 403-427 |
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I.Rojas, H.Pomares, J.Gonzalez, L.J.Herrera, A.Guillén, F.Rojas, O.Valenzuela "Adaptive fuzzy controller: Application to the control of the temperature of a dynamic room in real time" Fuzzy Sets and Systems, Elsevier 157 (2006) 2241 -2258. |
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J. González, I. Rojas, H. Pomares, Luis J. Herrera, A. Guillén, José M. Palomares, Fernando Rojas "Improving the accuracy while preserving the interpretability of fuzzy function approximators by means of multi-objective evolutionary algorithms" International Journal of Approximate Reasoning, Elsevier, 2007, IJA 6356, 44-1, pp. 32-44
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L. J. Herrera, H. Pomares, I. Rojas, A. Guillén, J. González, M. Awad, A. Herrera, "MultiGrid-Based Fuzzy Systems for Time Series Prediction: CATS Competition", Neurocomputing, Elsevier, 2007, 70 (2007) 2410-2425 |
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A. Guillén, I. Rojas, J. González, H. Pomares and L. J. Herrera, "Output Value-Based Initialization For Radial Basis Function Neural Networks", Neural Processing Letters, Springer, 2007, Volume 25, Number 3, pp. 209-225 |
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L. J. Herrera, H. Pomares, I. Rojas, A. Guillén, A. Prieto, O. Valenzuela: "Recursive Prediction for Long Term Time Series Forecasting Using Advanced Models", Neurocomputing, Elsevier, 2007, 70 (2007) 2870-2880 |
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A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera, O. Valenzuela and A. Prieto "Using Fuzzy Logic to Improve a Clustering Technique for Function Approximation" Neurocomputing, Elsevier, 2007, 70, 2853-2860 |
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O. Valenzuela, I.Rojas, F.Rojas, H. Pomares, L.J.Herrera, A. Guillén, B. Prieto, L.Marquez, M.Pasadas, "Hybridation of Intelligent Techniques and ARIMA Models for Time Series Prediction", Fuzzy Sets and Systems, Elsevier, 2008, 159, 821-845 |
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O. Valenzuela, I.Rojas, F.Rojas, A.Guillén, L.J.Herrera, H.Pomares, L.Marquez, M.Pasadas, "Soft-Computing techniques and ARMA model for time series prediction", Neurocomputing, Elsevier 2008, 71 (2008) 519-537 |
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A. Guillén H. Pomares I. Rojas J. González L.J. Herrera F. Rojas "Studying Possibility in a Clustering Algorithm for RBFNN Design for Function Approximation". Neural Computing & Applications journal, Springer, 2008, Volume 17 , Issue 1, pp. 75 - 89
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Olga Valenzuela, Ignacio Rojas, Francisco Javier Rojas, Héctor Pomares, José Luis Bernier, Luis Javier Herrera, Alberto Guillén: Intelligent System Based on Genetic Programming for Atrial Fibrillation Classification. Applied Artificial Intelligence 23(10): 895-909 (2009)
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Ghinea R, Pérez MM, Herrera LJ, Rivas MJ, Yebra A, Paravina RD.: Color difference thresholds in dental ceramics, J Dent. 2010, 38 Suppl 2:57-64. Epub 2010 Jul 27.
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Ginés Rubio, Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén: Design of specific-to-problem kernels and use of kernel weighted K-nearest neighbours for time series modelling. Neurocomputing 73(10-12): 1965-1975 (2010)
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Alberto Guillén, Luis Javier Herrera, Ginés Rubio, Héctor Pomares, Amaury Lendasse, Ignacio Rojas: New method for instance or prototype selection using mutual information in time series prediction. Neurocomputing 73(10-12): 2030-2038 (2010)
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Luis J. Herrera, Rosa Pulgar, Janiley Santana, Juan C. Cardona, Alberto Guillén, Ignacio Rojas, and María del Mar Pérez: Prediction of color change after tooth bleaching using fuzzy logic for Vita Classical shades identification, Applied Optics, Vol. 49, Issue 3, pp. 422-429 (2010)
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Alberto Guillén, F. G. del Moral, Luis Javier Herrera, Ginés Rubio, Ignacio Rojas, Olga Valenzuela, Héctor Pomares: Using near-infrared spectroscopy in the classification of white and iberian pork with neural networks. Neural Computing and Applications 19(3): 465-470 (2010)
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L.J. Herrera, H. Pomares, I. Rojas, A. Guillen and O. Valenzuela: The TaSe-NF model for function approximation problems: Approaching local and global modelling , Fuzzy Sets and Systems, Volume 171, Issue 1, 16 May 2011, Pages 1-21
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Selecci�n sobre congresos y otras publicaciones
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Herrera, L.J., Pomares, H., Rojas, I., Valenzuela, O., Awad, M., "MultiGrid-Based Fuzzy Systems for Function Approximation". Lecture notes in computer science, Springer Vol. 2972, ISBN 3-540-21459-3, pp.252-261, April 2004 |
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Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Mohammed Awad, "Analysis of the TaSe-II TSK-type Fuzzy System for function approximation", Lecture notes in computer science, Springer, ECSQARU'2005, pp 613-624 |
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Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Jesús González, and Mohammed Awad, "Clustering-Based TSK Neuro-Fuzzy Model for Function Approximation with Interpretable Sub-models", Lecture notes in computer science, Springer, IWANN'2005, pp. 399-406 |
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Tobias Jung, Luis J. Herrera, B. Schoelkopf, "Long Term Prediction of Product Quality in a Glass Manufacturing Process Using a Kernel Based Approach", Lecture notes in computer science, Springer, IWANN'2005, pp. 960-967 |
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L. J. Herrera, H. Pomares, I. Rojas, A. Guillén, M. Awad, and J. González, "Interpretable Rule Extraction and Function Approximation from numerical Input/Output Data Using the modified Fuzzy TSK model: TaSe model", RSFDGrC 2005, LNAI 3641, Springer, pp. 402-411, 2005. |
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A. Guillén, I. Rojas, J. González, H. Pomares and L. J. Herrera, O. Valenzuela and A. Prieto, "Improving Clustering Technique for Functional Approximation Problem using Fuzzy Logic: ICFA algorithm", Lecture notes in computer science, Springer, IWANN'2005, pp. 272-279 |
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L.J.Herrera, H.Pomares, I.Rojas, M.Verleysen, and A.Guillén "Effective Input Variable Selection for Function Approximation" Lecture notes in computer science, Springer, ICANN 2006, Part I, Vol. 4131, pp.41 -50, 2006. |
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A. Guillén, I. Rojas, J. González, H. Pomares, L.J. Herrera, and A. Prieto: "A Fuzzy-Possibilistic Fuzzy Ruled Clustering Algorithm for RBFNNs Design" RSCTC 2006, LNAI 4259, Springer, pp. 647-656 |
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A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera, B. Paechter "Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation through Parallel Islands Specialisation" Lecture notes in computer science, Springer, AI 2006, Vol. 4304, pp. 1127-1132 |
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A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera, B. Paechter, "Boosting The Performance Of A Multiobjective Algorithm To Design Rbfnns Through Parallelization", Lecture notes in computer science, Springer, ICANNGA'2007, Vol. 4431, pp. 85-92 |
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G. Rubio, H. Pomares, L.J. Herrera, I.Rojas, "Kernel Methods Applied To Time Series Forecasting", Lecture notes in computer science, Springer, IWANN 2007, Vol. 4507, pp. 773-780 |
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Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Ginés Rubio: On Incorporating Seasonal Information on Recursive Time Series Predictors. ICANN (2) 2007: 506-515 |
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Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Ginés Rubio, José M. Urquiza: Global and Local Modelling in Radial Basis Functions Networks. IWANN (1) 2009: 49-56 |
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Luis Javier Herrera, M. M. Pérez, J. Santana, R. Pulgar, Jesús González, Héctor Pomares, Ignacio Rojas Ruiz: A Data Mining Approach Based on a Local-Global Fuzzy Modelling for Prediction of Color Change after Tooth Bleaching Using Vita Classical Shades. ISDA 2009: 1268-1273 |
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José Miguel Urquiza Ortiz, Ignacio Rojas Ruiz, Héctor Pomares, Luis Javier Herrera, Ginés Rubio, J. P. Florido: Prediction of protein-protein interactions in yeast using SVMs with genomics/proteomics information and feature selection. ISCIS 2009: 645-650 |
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Luis Javier Herrera, Ginés Rubio, Héctor Pomares, Ben Paechter, Alberto Guillén, Ignacio Rojas: Strengthening the Forward Variable Selection Stopping Criterion. ICANN (2) 2009: 215-224 |
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Antonio Miguel Mora, Carlos M. Fernandes, Luis Javier Herrera, Pedro A. Castillo, Juan J. Merelo Guervós, Fernando Rojas, Agostinho C. Rosa: Sleeping with ants, SVMs, multilayer perceptrons and SOMs. ISDA 2010: 126-131 |
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Antonio Mora, Luis Javier Herrera, José Urquiza, Ignacio Rojas, J.J. Merelo: Applying Support Vector Machines and Mutual Information To Book Losses Prediction. IJCNN 2010: 984 - 990 |
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