List of Publications

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    Publications in Journals Fully Referred

  1. David Elizondo, Gerrit Hoogenboom, and R. W. McClendon. Neural Network Models for Prediction of Flowering and Physiological Maturity of Soybean. Transactions of the American Society of Agriculture Engineers (ASAE), volume 37, numéro 3, pages 981-988, 1994 (40 citations).
  2. David Elizondo, Gerrit Hoogenboom, and R. W. McClendon. Development of a Neural Network Model to Predict Daily Solar Radiation. Agricultural and Forest Meteorology, volume 71, pages 115-132. 1994 (39 citations).
  3. D. Elizondo and E. Fiesler. A Survey of Partially Connected Neural Networks. The International Journal of Neural Systems, volume 8, pages 535-558, 1997.
  4. M. Tajine and  D. Elizondo. The Recursive Deterministic Perceptron Neural Network. Neural Networks, volume 11, pages 1571-1588, 1998 (11 citations).
  5. M. Tajine, and D. Elizondo. Growing methods for constructing Recursive Deterministic Perceptron neural networks and knowledge extraction. Artificial Intelligence, volume 102, pages 295-322, 1998 (12 citations).
  6. M. Tajine, and D. Elizondo. New Methods for Testing Linear Separability. Neurocomputing volume 47, Issues 1-4, pages 295-322, August 2002 (5 citations).
  7. D. Elizondo. The Linear Separability Problem: Some Testing Methods. Transactions on Neural Networks (IEEE). 17(2):330-344, March 2006 (21 citations).
  8. Marcos Faundez-Zanuy, David A. Elizondo, Miguel-Angel Ferrer-Balleste, and Carlos M. Travieso-Gonzalez. Authentication of Individuals using Hand Geometry Biometrics: a Neural Network Approach. Neural Processing Letters, 26(3):201-216, December 2007 (9 citations).
  9. David A. Elizondo , Ralph Birkenhead, Mario Gongora, Eric Taillard and Patrick Luyima. Analysis and Test of Efficient Methods for Building Recursive Deterministic Perceptron Neural Networks. Neural Networks 20:1095-1108, 2007 (3 citations).
  10. Esteban Alfaro Cortes, Noelia Garcia Rubio, Matias Gamez Martinez and David A. Elizondo. Bankruptcy Forecasting: An Empirical Comparison of AdaBoost and Neural Networks. Decision Support Systems. 45:110-122, 2008 (14 citations).
  11. Elizondo, D. and Mattews, S. Recent Patents on Computational Intelligence. Recent Patents on Computer Science.  1:110-117, 2008.
  12. C. Bitter, D. Elizondo and Y. Yang, Natural Language Processing - A Prolog Perspective. Artificial Intelligence Review. 33(1-2):152-174 2010.
  13. David A. Elizondo, J.M. Ortiz-de-Lazcano-Lobato and Ralph Birkenhead. Choice effect of linear separability testing methods on constructive neural network algorithms: An empirical study. Expert Systems with Applications. Volume 38, Issue 3, March 2011, Pages 2330-2346.
  14. Eric Goodyer, Samad Ahmadi, Chiclana, Francisco, David Elizondo, Mario Gongora, Benjamin N. Passow, Yingjie Yang.Computational Intelligence and its role in enhancing sustainable transport systems.International Journal for Traffic and Transport Engineering (IJTTE), 1(3), 2011.
  15. Esteban José Palomo, John North, David Elizondo, Rafael M Luque and Tim Watson. Application of Growing Hierarchical SOM for Visualisation of Network Forensics Traffic Data. Neural Networks. Volume 32, August 2012, Pages 275–284. Selected Papers from IJCNN 2011.
  16. David A. Elizondo, R. Birkenhead, Matias Gamez, Noelia Garcia and Esteban Alfaro. Linear Separability and Classification Complexity. Expert Systems with Applications. Volume 39, Issue 9, July 2012, Pages 7796-7807.
  17. M. Piliougine Rocha, L. Mora Lopez, M. Sidrach de Cardona and D. A. Elizondo. Photovoltaic module simulation by neural networks using solar spectral distribution.: Progress in Photovoltaics: Research and Applications, 21 (5), pp. 1222-1235.
  18. Rafael Marcos Luque Baena, David Elizondo, Ezequiel López-Rubio, Esteban J Palomo and Tim Watson. Assessment of Geometric Features for Individual Identification and Verification in Biometric Hand Systems. Expert Systems with Applications. Volume 40, Issue 9, July 2013, Pages 3580–3594
  19. Frederic Magoules, Hai-xiang Zhao and David Elizondo. Development of an RDP Neural Network for Building Energy Consumption Fault Detection Diagnosis. Energy and Buildings Volume 62, July 2013, Pages 133–138.
  20. Michel Piliougine, David Elizondo, Llanos Mora-López and Mariano Sidrach-de-Cardona. Multilayer Perceptron Applied to the Estimation of the Influence of the Solar Spectral Distribution on Thin‐Film Modules . Applied Energy. Volume 112, December 2013, Pages 610–617.
  21. David A. Elizondo, Robert Morris, Tim Watson and Benjamin N. Passow. Constructing Recursive Deterministic Perceptron Neural Networks with Genetic Algorithms. International Journal of Pattern Recognition and Artificial Intelligence. Volume 27, Issue 06, September 2013.
  22. Esteban Palomo, David Elizondo and Gilles Brunschwig. Land Usage Classification: A Hierarchical Neural Network Approach. Journal of Agricultural Science. Volume 152, Issue 05, October 2014, Pages 817-828
  23. Ruiz-Rodado, V. ; Luque-Baena, R. M. ; te Vruchte, D. J. ; Probert, Fay ; Lachmann, R. H. ; Hendriksz, Christian J. ; Wraith, James E. ; Imrie, Jackie ; Elizondo, David ; Sillence, Daniel J. ; Clayton, P. ; Platt, Frances M. ; Grootveld, M. 1H NMR-Linked Urinary Metabolic Profiling of Niemann-Pick Class C1 (NPC1) Disease: Identification of Potential New Biomarkers using Correlated Component Regression (CCR) and Genetic Algorithm (GA) Analysis Strategies. Current Metabolomics, 2 (2), 2014 pp. 88-121
  24. Beatriz Garcia, Michel Piliougine, Jorge Aguilar and David Elizondo CPV module electric characterisation by artificial neural networks Renewable Energy. Volume 78, June 2015, Pages 173-181.
  25. Cristóbal J. Carmona, V. Ruiz-Rodado, M. J. del Jesus, A. Weber, M. Grootveld, P. González, D. Elizondo A fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans. Inf. Sci. 298: 180-197 2015.
  26. Ezequiel López-Rubio, David A. Elizondo , Martin Grootveld, José M. Jerez, and Rafael M. Luque-Baena. Computational Intelligence Techniques in Medicine . Computational and Mathematical Methods in Medicine, Hindawi, Volume 2015 (2015), Article ID 196976
  27. Michel Piliougine, David Elizondo , Llanos Mora-Lopez and Mariano Sidrach-de-Cardona Modelling Photovoltaic Modules with Multilayer Perceptrons using Angle of Incidence and Clearness Index Progress in Photovoltaics: Research and Applications, Volume 23, Pages 513-523, 2015.
  28. M. Torres-Ramírez, D. Elizondo , B. García-Domingo, G. Nofuentes and D.L. Talavera. Modelling the spectral irradiance distribution in sunny inland locations using an ANN-based methodology Energy. Accepted for Publication. April 2015.
  29. D. Elizondo , Shang-Ming Zhou, and Charalambos Chrysostomou Light Source Detection for Digital Images in Noisy Scenes: A Neural Network Approach Neural Computing and Applications. Accepted for Publication. March 2016.


    30. Edited Books

  30. Leonardo Franco, David Elizondo, Jose Jerez editors. Constructive Neural Network Algorithms. Series: Studies in Computational Intelligence , Vol. 258  2010, VIII, 294 p., Hard over, ISBN: 978-3-642-04511-0
  31. David Elizondo, Agusti Solanas, Antoni Martinez-Balleste editors. Computational Intelligence for Privacy and Security. Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.


    32. Book Chapters Fully Refereed

  32. D. Elizondo, M. Gongora. Current Trends on Knowledge Extraction and Neural Networks. In: W. Duch et al., editor, Lecture Notes in Computer Science, pages 485-490, September 2005.
  33. M. Gongora, T. Watson, D. Elizondo. A novel Method for Extracting Knowledge from Neural Networks with Evolving SQL Queries. In:  W. Duch et al., editor, Lecture Notes in Computer Science, pages 497-502, September 2005.
  34. David A. Elizondo, Benjamin N. Passow, Ralph Birkenhead, and Andreas Huemer. Dimensionality Reduction and Microarray data. In: A. Gorban et al., editor, Principal Manifolds. Springer, pages 293-307, February 2007.
  35. David Elizondo, Juan Miguel Ortiz-de-Lazcano-Lobato and Ralph Birkenhead. A Fast Method for Testing Linear Separability. In: W. Duch et al., editor, Lecture Notes in Computer Science, pages 737-746, September 2007.
  36. Andreas Huemer, David Elizondo and Mario Gongora. A Reward-Value Based Constructive Method for the Autonomous Creation of Machine Controllers. In: W. Duch et al., editor, Lecture Notes in Computer Science, pages 773-782, September 2008.
  37. David Elizondo, Shang-Ming Zhou and Charalambos Chrysostomou. Surface Reconstruction techniques using neural networks to  recover 3D scenes. In: W. Duch et al., editor, Lecture Notes in Computer Science, pages 857-866, September 2008.
  38. David A. Elizondo, Juan M. Ortiz-de-Lazcano-Lobato and Ralph Birkenhead. On the generalization of the m-class RDP Neural Network. In: W. Duch et al., editor, Lecture Notes in Computer Science, pages 734-743, September 2008.
  39. Andreas Huemer, David Elizondo and Mario Gongora. A Reward-Value Based Constructive Method for the Autonomous Creation of Machine Controllers (extended version). In:  Leonardo Franco, David Elizondo, Jose Jerez editors, Lecture Notes in Computer Science, Springer, January 2009.
  40. M. Do Carmo Nicoletti, J. Bertini, David Elizondo, L. Franco and J. Jerez. Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification tasks (extended version). In:  Leonardo Franco, David Elizondo, Jose Jerez editors, Lecture Notes in Computer Science, Springer, January 2009.
  41. David A. Elizondo, Juan M. Ortiz-de-Lazcano-Lobato and Ralph Birkenhead. On the generalization of the m-class RDP Neural Network (extended version). In:  Leonardo Franco, David Elizondo, Jose Jerez editors, Lecture Notes in Computer Science, Springer, January 2009.
  42. David Elizondo, Agusti Solanas, Antoni Martinez-Balleste editors. Introduction to Computational Intelligence for Privacy and Security. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  43. Bernd Stahl, David Elizondo, Moira Carroll-Mayer, Yingqin Zheng and Kutoma Wakunuma. Ethical and Legal Issues of the Use of Computational Intelligence Techniques in Computer Security and Computer Forensics. Extended version. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  44. E.J. Palomo, D. Elizondo, E. Dominguez, R.M. Luque and T. Watson. SOM-based Techniques towards Hierarchical Visualisation of Network Forensics Traffic Data. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  45. R. M. Luque, D. Elizondo, E. Lopez-Rubio, and E.J. Palomo. Feature Selection of Hand Biometrical Traits based on Computer Intelligence Techniques. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  46. S. Alamro, D. Elizondo, A. Solanas and A. Martinez. Applications of Evolutionary Computing towards Computer Security and Forensics. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  47. S. Alamro, F. Chiclana and D. Elizondo . Applications of Fuzzy Logic towards Computer Security and Forensics. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  48. D. Elizondo , A. Solanas and M Martinez-Ballestero. Computational Intelligence for Privacy and Security. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  49. Christian Bitter, John North, David A. Elizondo and Tim Watson. An Introduction to the Use of Neural Networks for Network Intrusion Detection. Book chapter Springer Series: Studies in Computational Intelligence , Vol. 394  2012, 260 p., Hard over, ISBN 978-3-642-25236-5 Due: January 2012.
  50. Leigh, Roland James; Wells, Alan; Monks, Paul S; Passow, Ben N; Elizondo, David; Goodyer, Eric; Gustafsson, Stefan Managing air quality: Systems for future cities. In: 50 Uses of GMES across European Regions. Network of European Regions Using Space Technology (NEREUS)/European Space Agency (ESA), April 2012


    51. Publications in International and National Conferences with Reading Committee

  51. David Elizondo, Gerrit Hoogenboom, and R. W. McClendon. Neural Network Models for Predicting Crop Phenology. In Proceedings of the International winter meeting of the American Society of Agriculture Engineers (ASAE). Nashville Tenessee, December 1992.
  52. D. Elizondo, E. Fiesler, and J. Korczak. Non-Ontogenic Sparse Neural Networks. IEEE International Conference in Neural Networks (ICNN-95), Perth, Australia, No 26, 1er December 1995 (5 citations).
  53. M. Tajine, D. Elizondo, E. Fiesler, and J. Korczak. The Class of Linear Separability Method. The European Symposium on Artificial Neural Networks (ESANN-97), Bruges (Belgium), 16-17-18 April 1997.
  54. M. Tajine, D. Elizondo, E. Fiesler, and J. Korczak. Adapting the Recursive Deterministic Perceptron Neural Network to m-classes. The International Conference on Neural Networks (ICNN-97), Houston, Texas, 9-12 June 1997.
  55. D. Elizondo. Searching for Linearly Separable Subsets using the Class of Linear Separability Method. In: IEEE-International Joined Conference in Neural Networks, pages 955-960, Budapest, 25-29,  April 2004 (5 citations).
  56. David Elizondo, Ralph Birkenhead, and Eric Taillard. Generalisation and the Recursive Deterministic Perceptron. IEEE International Joined Conference on Neural Networks, July 2006.
  57. Huemer, A., Gongora, M. and Elizondo, D. Evolving a Neural Network Using Dyadic Connections. In: Proc. International Joint Conference on Neural Networks (IJCNN 2008), Hong Kong, June 2008. Accepted for Publication.
  58. Huemer, A. Gongora, M., Elizondo, D. Self Constructing Neural Network Robot Controller Based on On-line Task Performance Feedback. In: Proc. 5th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Madeira, Portugal, May 2008 (1 citation).
  59. David A. Elizondo and Hussam Hamrawi. A convergence upper bound for the Perceptron algorithm. UKCI-2008, Leicester, UK, September 2008.
  60. David A. Elizondo, Ralph Birkenhead, Noelia Garcia Rubio and Matias Gamez Martinez. Artificial Neural Networks for the measure of the complexity of classification problems. IJCNN-2009.
  61. Bernd Stahl, David Elizondo, Moira Carroll-Mayer, Yingqin Zheng and Kutoma Wakunuma. Ethical and Legal Issues of the Use of Computational Intelligence Techniques in Computer Security and Computer Forensics. IJCNN-2010, Barcelona, Spain, July 2010.
  62. Christian Bitter, David Elizondo and Tim Watson. Application of Artificial Neural Networks and Related Techniques to Intrusion DetectionIJCNN-2010, Barcelona, Spain, July 2010.
  63. Andreas Huemer, Mario Gongora and David Elizondo. A  Robust Reinforcement based Self Constructing Neural Network . IJCNN-2010, Barcelona, Spain, July 2010.
  64. E.J. Palomo, J. North, D. Elizondo, R.M. Luque and T. Watson. Visualisation of Network Forensics Traffic Data with a Self-Organising Map for Qualitative Features. IEEE IJCNN-2011. San Jose, California, July 2011.
  65. Rafael Marcos Luque, David Elizondo, Ezequiel Lopez-Rubio and Esteban Jose Palomo. GA-based Feature Selection Approach in Biometric Hand Systems. IEEE IJCNN-2011. San Jose, California, July 2011.
  66. Eric Goodyer, Samad Ahmadi, Francisco Chiclana, David Elizondo, Mario Gongora, Benjamin N. Passow and Yingjie Yang. Delivery of Intelligent Transport Systems through the Application of Computational IntelligenceThe International Conference on Climate Friendly Transport. Shaping Climate Friendly Transport in Europe. REACT CONFERENCE, Belgrade, Serbia, 2011.
  67. Eric Goodyer, Samad Ahmadi, Francisco Chiclana, Andy Collop, David Elizondo, Mario Gongora, Benjamin N. Passow, Tim Watson, Yingjie Yang. Computational intelligence and its role in enhancing sustainable transport systems Transportation infrastructure & surface analysis ECU design & development, including exploitation of GNSS & telematics The Cyber Security Centre (CSC) THE-ISSUE Regions of Knowledge FP7 conference - European Launch, National Space Centre Leicester, January 2012.
  68. Benjamin N. Passow, David Elizondo, Eric Goodyer, Roland J. Leigh, James P. Lawrence, Satish Shah, Jolanta Obszynska, Sarah Brown, Stefan Gustafsson, Norbert Huebner. iTRAQ - An Integrated Traffic Management and Air Quality Control System Using Space Services Toulouse Space Show 2012. Toulouse, France, 25-28 June 2012.
  69. Sylvain Contassot-Vivier, David Elizondo. A near linear algorithm for testing linear separability in two dimensions. 13th Engineering Applications of Neural Network Conference (EANN2012), to be held in London, UK, from Sept. 20th to 23rd, 2012
  70. Michel Piliougine, David Elizondo, Llanos Mora-López and Mariano Sidrach-de-Cardona. Multilayer Perceptron Applied to the Estimation of the Influence of the Solar Spectral Distribution on Thin‐Film Modules . ICAE-2012, July 5-8, 2012 Suzhou, China.
  71. Benjamin Passow, David Elizondo , Francisco Chiclana, Simon Witheridge and Eric Goodyer Adapting Traffic Simulation for Traffic Management: A Neural Network Approach International IEEE Annual Conference on Intelligent Transportation Systems.
  72. Pamela Hardaker, Benjamin N. Passow and David Elizondo. Walking State Detection from Electromyographic Signals towards the Control of Prosthetic Limbs UKCI 2013
  73. M. Torres-Ramírez, B. García-Domingo, D. Elizondo , G. Nofuentes, D. L. Talavera. Comparative analysis of methods for estimating the average photon energy: The case of study of a sunny site 28th EU PVSEC 2014, 22-26 September 2014, Amsterdam.
  74. D. Paluszczyszyn, M. Al-Doori, W. Manning, D. Elizondo, and E. Goodyer. Range extended engine management system for electric vehicles: Control design process. In AVEC14: 12th International Symposium on Advanced Vehicle Control, pages 468-473, 2014.
  75. M. Al-Doori, D. Paluszczyszyn, D. Elizondo, B. Passow, and E. Goodyer. Range extended for electric vehicle based on driver behaviour. In HEVC2014: The 5th IET Hybrid and Electric Vehicles Conference, 2014.
  76. Hardaker, Pamela ; Passow, Benjamin N. ; Elizondo, David. Multiple sensor outputs and computational intelligence towards estimating state and speed for control of lower limb prostheses. UKCI 2014.
  77. Alexis Le Compte, Tim Watson and David Elizondo. A Renewed Approach to Serious Games for Cyber Security NATO CCD COE 7th International Conference on Cyber Conflict. 26-29 May 2015, Tallinn.
  78. Hasshu, S., Chiclana, F., Passow, B. N. and Elizondo, D. Encouraging Active Commuting through monitoring and analysis of commuter travel method habits , in the SAI Intelligent Systems Conference (IntelliSys'15), pp. 179-186, DOI:10.1109/IntelliSys.2015.7361142, London, UK, 2015.
  79. David Elizondo., Conor Fahy and Pamela Hardaker. OPTIcut: A strategic tool for banana stem optimisation and development of market strategies Sixth International Banana Congress and XXI International Meeting ACORBAT. 19-22 April 2016, Miami, Florida, USA.
  80. N. Khan, D. Elizondo, B. N. Passow and P. Hardaker, Pose invariance through registration for hierarchical feature based pattern recognition systems, 2017 International Joint Conference on Neural Networks (IJCNN), Anchorage, AK, 2017, pp. 2902-2910. doi: 10.1109/IJCNN.2017.7966215
  81. Elizondo, D. and Orun, A. An Intelligent traffic network optimisation by use of Bayesian inference methods to combat air pollution , TPM- Transport Practitioner’s Meeting Conference, 28-29 June 2017, Nottingham


    82. Publications  in conferences without reading committee

  82. M. Tajine and D. Elizondo. Approches Géométriques pour les réseaux de neurones  artificiels. AFIG-97, Rennes, France 3, 4, 5 December 1997.


    83. Thesis

  83. D. Elizondo. Neural Networks Models to Predict Solar Radiation and Plant Phenology. MSc Thesis, University of Georgia, Athens, Georgia, USA 1992.
  84. D. Elizondo. Process control application of neural networks in a dynamic environment DEA in Computer Science, Université de Montpellier, Montpellier, France 1993.
  85. D. Elizondo. The Recursive Deterministic Perceptron and Topology Reduction Strategies for Neural Networks. PhD Thesis, Université Louis Pasteur, Strasbourg, France, 1997.
  86. D. Elizondo. Artificial Neural Networks, Theory and Applications. Habilitation Post-Doctoral Thesis, Université Franch-Comte, Belfort, France, 2008.


    87. Technical Reports

  87. M. Tajine and D. Elizondo. Geometrical properties of the Recursive Deterministic Perceptron neural networks. Technical report 97/17, Université Louis Pasteur, Dept. Info. 7 rue René Descartes, 67084, Strasbourg, France, 1997.
  88. M. Tajine and D. Elizondo. Enhancing the perceptron neural network by using functional composition. Technical report 96/07, Université Louis Pasteur, Dept. Info. 7 rue René Descartes, 67084, Strasbourg, France, 1996.
  89. D. Elizondo. A pruning method for reducing the number of models in PCA Neural Networks. Technical Report. Neural Systems Limited, Plymouth, UK. 1998.
  90. D. Elizondo. Selection of Homogeneous Data Sets for Building Principal Component Analysis Based Neural Networks. Technical Report. Neural Systems Limited, Plymouth, UK. 1999.
  91. D. Elizondo. Minimization of Mixed Data Batches while Building PCA Neural Network Models. Technical Report. Neural Systems Limited, Plymouth, UK. 1999.
  92. D. Elizondo. Processing input data for Principal Component Analysis Neural Network Models. Technical Report. Neural Systems Limited, Plymouth, UK. 2000.
  93. Carmona, C. J.; Elizondo, David, Subgroup Discovery trhough Evolutionary Fuzzy Systems applied to Bioinformatic problems.  Technical Report. De Montfort University, Leicester, 2017
  94. Carmona, C. J. ; Elizondo, David, Subgroup Discovery: Real-World Applications. Technical Report. De Montfort University, Leicester, 2017
  95. Carmona, C. J. ; Elizondo, David, Supervised Descriptive Rule Discovery: A Survey of the State-of-the-Art.  Technical Report. De Montfort University, Leicester, 2017


    96. Publications Submitted

  96. James Wheeler, David A. Elizondo, Yingjie Yang and Eric Goodyear. Computational Intelligence used in Traffic and Air Pollution: Current State of the Art. IEEE Transactions on Intelligent Transportation Systems. Submitted September 2010.
  97. John North, Ollie Whitehouse, David Elizondo and Tim Watson. Eliminating Entropy To Identify Memory Revelations Computer: Special Issue on Cybersecurity. Submitted November 2012.
  98. A. Huemer, H. Kimbal, D. A. Elizondo and M. Gongora. Recent Advances in Self-Constructing Neural Networks for Machine Control on Single Agents. Neural Processing Letters. Submitted April 2013.
  99. Benjamin N. Passow, David Elizondo, Francisco Chiclana, and Eric Goodyer. A Spatially Distributed and Adaptive Predictor Network for Near-Real-Time Traffic Simulation and Management IEEE Transactions on Neural Networks. Submitted May 2012.
  100. Frederic Magoules, Michel Piliougine and David Elizondo. Support Vector Regression for Electricity Load Forecast Applied Energy. Submitted December 2013.
  101. Beatriz Garcia, Michel Piliougine, David Elizondo and Jorge Aguilar Multilayer perceptron models to predict the I-V curve of concentrating photovoltaic modules Progress in Photovoltaics. Submitted June 2014.
  102. Frederic Magoules, Hai-xiang Zhao, Michel Piliougine, and David Elizondo New Parallel Support Vector Machines on a Multi-Core System. Expert Systems with Applications. January 2015.