Listado de Publicaciones



A) Publicaciones como autor principal

(Papers as main author)

a) Artículos en revistas citadas en el ISI

(Papers with citation index)
  1. 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, IWANN’2005, pp. 272-279 - [PDF] - [BibTex]

  2. A. Guillén, I. Rojas, J. González, H. Pomares, L.J. Herrera, O. Valenzuela, and A. Prieto, "A Possibilitic Approach to RBFN Centers Initialization", RSFDGrC 2005,LNAI 3642,pp.174 –183,2005. - [PDF] - [BibTex]

  3. A. Guillén, I. Rojas, E. Ros, L. J. Herrera: "Using Fuzzy Clustering Technique for Function Approximation to Approximate ECG Signals". IWINAC (2) 2005: 538-547 - [PDF] - [BibTex]

  4. A. Guillén, I. Rojas, J. González, H. Pomares, L.J. Herrera and Francisco Fernández: "Multiobjective RBFNNs Designer for Function Approximation: An Application for Mineral Reduction" LNCS 4221, pp.511-520,2006 - [PDF] - [BibTex]

  5. 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, pp.n 647-656 - [PDF] - [BibTex]

  6. A. Guillén, I. Rojas, J. González, H. Pomares and L. J. Herrera, O. Valenzuela and A. Prieto "Using Fuzzy Logic to Improve a Clustering Technique for Function Approximation" Neurocomputing DOI: 10.1016/j.neucom.2006.06.017 - [PDF] - [BibTex]

  7. 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" LNAI 4304, pp 1127-1132, 2006 - [PDF] - [BibTex]

  8. A. Guillén H. Pomares I. Rojas J. González L.J. Herrera F. Rojas, O. Valenzuela "Studying Possibility in a Clustering Algorithm for RBFNN Design for Function Approximation". Neural Computing & Applications journal, DOI: 10.1007/s00521-007-0134-6 - [PDF] - [BibTex]

  9. A. Guillén H. Pomares I. Rojas J. González L.J. Herrera F. Rojas, O. Valenzuela "Output value-based initialization for radial basis function neural networks", Neural Processing Letters, DOI: 10.1007/s11063-007-9039-8 - [PDF] - [BibTex]

  10. A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera, A. Prieto "Parallel Multi-objective Memetic RBFNNs Design and Feature Selection for Funtion Approximation Problems" LNCS 4507, pp. 341-350,2007 - [PDF] - [BibTex]

  11. A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera "A First Approach to Birth Weight Prediction Using RBFNN" LNCS 4527, pp. 253-260, 2007 - [PDF] - [BibTex]

  12. A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera, B. Paechter "Boosting the Performance of a Multiobjective Algorithm to Design RBFNN Through Paralleization" LNCS 4431, pp 85-92, 2007 - [PDF] - [BibTex]

b) Artículos en revistas de reconocida relevancia

  1. A.Guillén, I.Rojas, J.González, H. Pomares, L.J. Herrera Maldonado, Clustering Based Algorithm for RBF Centres Initialization. Fuzzy Economic Review, Vol X(2): 27-45, November 2005. - [PDF] - [BibTex]

c) Publicaciones en actas de congresos internacionales

  1. A. Guillén, I. Rojas, J. González, H. Pomares and L.J. Herrera: "Supervised RBFNN Centers and Radii Initialization for Function Approximation Problems"2006 IEEE World Congress on Computational Intelligence, pp. 5814-5819, 2006.

  2. A.Guillén, I.Rojas, J.González, H. Pomares, L.J. Herrera Maldonado, Clustering Based Algorithm for RBF Centres Initialization. XI SIGEF Congress, Techniques and Methodologies for the Information and Knowledge Economy, ISBN 88-8296-146-X, November 2004, Reggio Calabria-Messina, pp. 44-63.

  3. A.Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera and A. Prieto, Using a New Clustering Algorithm to Design RBF Networks for Functional Approximation Problems. Proceedings of the Learning'04 International Conference, ISBN 84-688-8453-7, Elche, Spain, October 2004, pp. 19-24.

  4. A. Guillén, J. González, I. Rojas, H. Pomares, L.J. Herrera, F. Fernandez "A New Multiobjective RBFNNs Designer and Feature Selector for a Mineral Reduction Application". FUZZ-IEEE, 2007, Londres.

d) Publicaciones en actas de congresos nacionales

  1. A. Guillén, I. Rojas, J. Gonzalez, H. Pomares, L.J. Herrera, O. Valenzuela "Revising Clustering Technique for Functional Approximation Problem using Fuzzy Logic", CEDI’2005 - SIMPOSIO DE INTELIGENCIA COMPUTACIONAL (SICO’2005),. IEEE Computational Intelligence Society SC. Editorial Thomson, Septiembre 2005.

  2. A.Guillén, I.Rojas, J.González, L.J.Herrera, H.Pomares, A.Prieto, Inicialización de Centros RBFs Utilizando Clustering para Problemas de Aproximación Funcional, Actas del XII Congreso Español sobre Tecnologías y Lógica Difusa, ESTYLF2004, ISBN 84-609-2160-3, Jaén, septiembre 2004, pp. 605-610

  3. A.Guillén, I.Rojas, J.González, H.Pomares, L.J.Herrera, A.Prieto Interfaz para MATLAB y bibliotecas de paso de mensajes: MPIMEX, CEDI’2007 - SIMPOSIO DE INTELIGENCIA COMPUTACIONAL (SICO’2007),. IEEE Computational Intelligence Society SC. Editorial Thomson, Septiembre 2007.

B) Publicaciones como autor colaborador

a) Artículos en revistas citadas en el ISI

  1. L. J. Herrera, H. Pomares, I. Rojas, and A. Guillén, "TaSe model for Long Term Time Series Forecasting", Lecture Notes in Computer Science, IWANN’2005, pp 1027-1034

  2. L. J. Herrera, H. Pomares, I. Rojas, A. Guillén, J. González, and Mohammed Awad, "Clustering-Based TSK Neuro-Fuzzy Model for Function Approximation with Interpretable Sub-models", Lecture Notes in Computer Science, IWANN’2005, pp. 399-406

  3. M. Awad, H. Pomares, L.J. Herrera , J. González, A. Guillén and F. Rojas, "Approximating I/O data using Radial Basis Functions: A new clustering-based approach", IWANN’2005, pp. 289-296

  4. L. J. Herrera, H. Pomares, I. Rojas, A. Guillén, Mohammed Awad, "Analysis of the TaSe-II TSK-type Fuzzy System for function approximation", Lecture Notes in Computer Science, ECSQARU’2005, pp 613-624

  5. L. Herrera Maldonado, H. Pomares, I. Rojas, A. Guillén-Perales, "New Clustering Technique for Inicialization of Centres in TSK Clustering-Based Fuzzy Systems", Lecture Notes in Computer Science, ECSQARU’2005, pp, 980-991

  6. 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,

    7. pp. 402–411, 2005.
  7. G. Rubio, H. Pomares, I. Rojas, A. Guillén: "A Basic Approach to Reduce the Complexity of a Self-generated Fuzzy Rule-Table for Function Approximation by Use of Symbolic Regression in 1D and 2D Cases". IWINAC (2) 2005: 143-152

  8. L.J.Herrera, H.Pomares, I.Rojas, M.Verleysen, and A.Guilén "Effective Input Variable Selection for Function Approximation" ICANN 2006, Part I, LNCS 4131, pp.41 –50, 2006.

  9. 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 157 (2006)2241 –2258.

  10. L. J. Herrera Maldonado, H. Pomares, I. Rojas, A. Guillén, A. Prieto, O. Valenzuela "Recursive Prediction for Long Term Time Series Forecasting Using Advanced Models" Neurocomputing, DOI: 10.1016/j.neucom.2006.04.015

  11. 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, vol 44,32-44,2007

  12. 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, DOI: 10.1016/j.neucom.2006.09.14

  13. L.J. Herrera, H. Pomares, I. Rojas, A. Guillén, "On Incorporating Seasonal Information on Recursive Time Series Predictors", LNCS, ACEPTADO

  14. O. Valenzuela, I. Rojas, F. Rojas, A. Guillén, L.J. Herrera, H. Pomares, L. Marquez, M. Pasadas, "Sofá-Computing techniques and ARMA model for time series prediction", Neurocomputing, ACEPTADO

b) Publicaciones en congresos internacionales

  1. 28.I.Rojas, H.Pomares, J.Gonzalez, L.J.Herrera, A.Guillén, F.Rojas "Soft-computing techniques for the development of adaptive helicopter flight controller", 2006. 9th IEEE International Workshop on Advanced Motion Control, March 2006, pp. 709- 714.

  2. J. González, I. Rojas, H. Pomares, L.J. Herrera, A. Guillén, "Multiobjetive Evolutionary design of Fuzzy Systems", I Workshop on genetic Fuzzy Systems (GFS’2005), pp. 22-29.

  3. O. Valenzuela, L.Marquez, M.Pasadas,I.Rojas, F.Rojas, A.Guillén, L.J. Herrera, "Time series approximation using linear and non-linear method", Mamern’2005, May 9-11, Morocco.

  4. O. Valenzuela, I.Rojas, A.Guillén, L.J. Herrera, H.Pomares, C. Atae-Allah, L.Marquez, "Classification of Prostate Cancer using Non-Linear Paradigms and Mutual Information", Mamern’2005, May 9-11, Morocco.

  5. I. Rojas, H. Pomares, J. González, L.J. Herrera, A. Guillen, O. Valenzuela, "Self-adaptive robot control using Fuzzy Logia", IEEE AMC, Estambul, 2006.

  6. O. Valenzuela, I.Rojas, L.J. Herrera, A.Guillén, F.Rojas, L. Marquez and M. Pasadas"Feature Selection using Mutual Information and Neural Networks" Ninth International Conference Zaragoza-PAU on Applied Mathematics and Statistics,pp. 331-340,2006

  7. L. J. Herrera, H. Pomares, I. Rojas, A. Guillén, G. Rubio, "Incorporating Seasonal Information on Direct and Recursive Predictors Using LS-SVM", European Symposium on Time Series Prediction, Espoo, Finlandia,2007,pp.155-164

  8. L. J. Herrera, H. Pomares, I. Rojas, A. Guillén, G. Rubio, "Removing seasonality on time series, a practical case", European Symposium on Time Series Prediction, Espoo, Finlandia,2007,pp.279-286

c) Publicaciones en congresos nacionales

  1. 41.O. Valenzuela, F. Rojas, H. Pomares, L.J. Herrera, A. Guillén, L. Márquez, "Lógica difusa para el análisis de series temporales: estudio de la estacionalidad", Simposio de Inteligencia Computacional SICO’ 2005. IEEE Computational Intelligence Society SC. Editorial Thomson, Septiembre 2005.

  2. L.J. Herrera, H. Pomares, I. Rojas, A. Guillén, J. González, Análisis estadístico del uso de reglas Takagi-Sugeno-Kang de orden alto en el diseño del proceso de inferencia difusa, Actas del XII Congreso Español sobre Tecnologías y Lógica Fuzzy, ESTYLF’2004, ISBN 84-609-2160-3, Jaén Septiembre 2004, pp.363-368