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Special Issue Cover

A new special issue on Fuzzy Approaches in Preference Modelling, Decision Making and Applications (International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems [IJUFKS]) has been edited by F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera.

 

               Int. Journals: J.M. Benítez

Number Of Publications: 24 Jump to Graph

Jump to Year: 2013 (1), 2012 (5), 2011 (3), 2010 (3), 2009 (1), 2008 (2), 2007 (2), 2004 (1), 2003 (1), 2002 (1), 2000 (1), 1998 (1), 1997 (1), 1996 (1)

Bolita Year 2013 (1):

Bolita In Press:

Bolita[1561] R. García, J.M. Benítez, G.I. Sainz-Palmero, FRASel: A Consensus of feature ranking methods for time series modelling. Soft Computing, in press (2013).

Bolita Year 2012 (5):

Bolita[1550] C. Bergmeir, I. Triguero, D. Molina, J.L. Aznarte M., J.M. Benítez, Time Series Modeling and Forecasting Using Memetic Algorithms for Regime-switching Models. IEEE Transactions on Neural Networks and Learning Systems (2012), volume 23, issue 11, pages 1841-1847 doi:10.1109/TNNLS.2012.2216898. iconPdf.png

Bolita[1506] J.L. Aznarte M., J. Alcalá-Fdez, A. Arauzo, J.M. Benítez, Financial Time Series Forecasting with a Bio-inspired Fuzzy Model. Expert Systems with Applications 39:16 (2012) 12302–12309. iconPdf.png

Bolita[1464] C. Bergmeir, M. García-Silvente, J.M. Benítez, Segmentation of Cervical Cell Nuclei in High-resolution Microscopic Images: A new Algorithm and a Web-based Software Framework. Computer Methods and Programs in Biomedicine 107(3) (2012) 497-512.

Bolita[1472] C. Bergmeir, J.M. Benítez, On the Use of Cross-validation for Time Series Predictor Evaluation. Information Sciences 191 (2012) 192-213.

Bolita[1438] C. Bergmeir, J.M. Benítez, Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS. Journal of Statistical Software 46(7) (2012) 1-26.

Bolita Year 2011 (3):

Bolita[1437] A. Araúzo-Azofra, J.L. Aznarte M., J.M. Benítez, Empirical study of feature selection methods based on individual feature evaluation for classification problems. Expert Systems with Applications, 38:7 (2011), 8170--8177.

Bolita[1436] J.L. Aznarte M., D. Molina, A.M. Sánchez, J.M. Benítez, A test for the homoscedasticity of the residuals in fuzzy rule-based models. Applied Intelligence, 34:3 (2011), 386--393.

Bolita[1279] J.L. Aznarte M., J. Alcalá-Fdez, A. Arauzo, J.M. Benítez, Fuzzy autoregressive rules: Towards linguistic time series modeling. Econometric Reviews 30:6 (2011) 609–631, doi: 10.1080/07474938.2011.553569. iconPdf.png

Bolita Year 2010 (3):

Bolita[1289] J.L. Aznarte M., J.M. Benítez , Equivalences between neural-autoregressive time series models and fuzzy systems. IEEE Transactions on Neural Networks, Vol. 21, No. 9 (2010), 1434-1445. 10.1109/TNN.2010.2060209. iconPdf.png

Bolita[1288] J.L. Aznarte M., Marcelo C. Medeiros, J.M. Benítez , Testing for Remaining Autocorrelation of the Residuals in the Framework of Fuzzy Rule-Based Time Series Modelling. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 18(4), pp. 371-387,doi:10.1142/S021848851000660X. iconPdf.png

Bolita[1193] J.L. Aznarte M., M.C. Medeiros, J.M. Benítez, Linearity testing against a fuzzy rule-based model. Fuzzy Sets and Systems Volume 161, Issue 13, 1 July 2010, Pages 1836-1851 doi:10.1016/j.fss.2010.01.00. iconPdf.png

Bolita Year 2009 (1):

Bolita[1079] I. Robles, R. Alcalá, J.M. Benítez, F. Herrera, Evolutionary Parallel and Gradually Distributed Lateral Tuning of Fuzzy Rule-Based Systems. Evolutionary Intelligence 2 (2009) 5-19, doi: 10.1007/s12065-009-0025-0. iconPdf.png

Bolita Year 2008 (2):

Bolita[0971] J.R. Ruiz, J. Ramirez-Lechuga, F.B. Ortega, J. Castro-Piñero, J.M. Ben�tez, A. Arauzo-Azofra, C. Sanchez, M. Sjöström, M.J. Castillo, A. Gutierrez, M. Zabala, Artificial neural network-based equation for estimating VO2max from the 20 m shuttle run test in adolescents. Artificial Intelligence in Medicine 44:3 (2008) 233-245, doi:10.1016/j.artmed.2008.06.004. iconPdf.png

Bolita[0824] A. Araúzo, J.M. Benítez, J.L. Castro, Consistency measures for feature selection. Journal of Intelligent Information Systems 30:3 (2008) 273-292, doi:10.1007/s10844-007-0037-0. iconPdf.png

Bolita Year 2007 (2):

Bolita[0822] J.L. Aznarte, J.M. Benítez, J.L. Castro, Smooth Transition Autoregressive Models and Fuzzy Rule-based Systems: Functional Equivalence and Consequences. Fuzzy Sets and Systems 158 (2007) 2734-2745, doi:10.1016/j.fss.2007.03.021. iconPdf.png

Bolita[0823] J.L. Aznarte, D. Nieto Lugilde, J.M. Benítez, F. Alba Sánchez, C. de Linares Fernández, Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models. Expert Systems with Applications 32 (2007) 1218-1225, doi:10.1016/j.eswa.2006.02.011. iconPdf.png

Bolita Year 2004 (1):

Bolita[0959] J.F. Fernández-Sánchez, A. Segura, J.M. Ben�tez, C. Cruces-Blanco, A. Fernández-Gutiérrez, Fluorescence optosensor using an artificial neural network for screening of polycyclic aromatic hydrocarbons. Analytica Chimica Acta 510 (2004) 183–187, doi: 10.1016/j.aca.2004.01.012. iconPdf.png

Bolita Year 2003 (1):

Bolita[0001] R. Alcalá, J.M. Benítez, J. Casillas, O. Cordón, R. Pérez, Fuzzy Control of HVAC Systems Optimized by Genetic Algorithms. Applied Intelligence 18:2 (2003) 155-177, doi: 10.1023/A:1021986309149. iconPdf.png

Bolita Year 2002 (1):

Bolita[0821] J.L. Castro, C.J. Mantas, J.M. Benítez, Interpretation of Artificial Neural Networks by means of Fuzzy Rules. IEEE Transactions on Neural Networks 13:1 (2002) 101-116, doi:10.1109/72.977279. iconPdf.png

Bolita Year 2000 (1):

Bolita[0820] J.L. Castro, C.J. Mantas, J.M. Benítez, Neural Networks with a Continuous Increasing Squashing function in the output are Universal Approximators. Neural Networks 13:6 (2000) 561-563, doi:10.1016/S0893-6080(00)00031-9. iconPdf.png

Bolita Year 1998 (1):

Bolita[0819] J.M. Benítez, A. Blanco, M. Delgado, I. Requena, New Aspects on Extraction of Fuzzy Rules using Neural Networks. Mathware & Soft Computing 5 (1998) 333-343. iconPdf.png

Bolita Year 1997 (1):

Bolita[0818] J.M. Benítez, J.L. Castro, I. Requena, Are Artificial Neural Networks Black Boxes?. IEEE Transactions on Neural Networks 8:5 (1997) 1156-1164, doi:10.1109/72.623216. iconPdf.png

Bolita Year 1996 (1):

Bolita[0817] J.M. Benítez, A. Blanco, M. Delgado, I. Requena, Neural Methods for Obtaining Fuzzy Rules. Mathware & Soft Computing 3 (1996) 371-382. iconPdf.png

 

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