Scientific publications

 

Scientific publications

Most recent or relevant:

In preparation:

Other works (by reverse chronological order):

  • Bernardete Ribeiro, Catarina Silva, Armando Vieira, A Gaspar-Cunha, Joao Carvalho Neves, "Financial Distress Model Prediction using SVM+", accepted at World Conference on Computational Information, Barcelona, 2010.
  • B. Ribeiro, C. Silva, A. S. Vieira and J. C. Neves, "Extracting Discriminative Features Using Non-Negative Matrix Factorization in Financial Distress Data", Proceeding of the International Conference on Artificial Neural Networks and Genetic Algorithms, Springer Lectures on Computer Science, ICANNGA 2009, Kuopio, Finland, 2009.
  • A. S. Vieira, João Duarte, B. Ribeiro and J. C. Neves, "Accurate Prediction of Financial Distress with Machine Learning Algorithms", Proceeding of the International Conference on Artificial Neural Networks and Genetic Algorithms, Springer Lectures on Computer Science, ICANNGA 2009, Kuopio, Finland, 2009.
  • Ning Chen and Armando Vieira "Bankruptcy prediction based on independent component analysis", International Conference on Agents and Artificial Intelligence, ICAART, Porto 2009.
  • D. Smeets, N. P. Barradas, A. Vieira, J. Demeulemeester, C. M. Comrie, C. Theron and A. Vantomme, "Real-time RBS to study thin film growth kinetics: the use of artificial neural networks for instantaneous data analysis", 14th International Conference on Thin Films & Reactive Sputter Deposition  2008, ICTF.
  • D. Smeets, N. P. Barradas, A. Vieira, J. Demeulemeester, C. M. Comrie, C. Theron and A. Vantomme, "Instantaneous Analysis of Real-Time RBS Data Using Artificial Neural Networks",Proceedings of the 20th International Conference on the Application of Accelerators in Research and Industry, CAARI, 2008
  • Ribeiro, B.,  Vieira, A. and Neves, J. , Supervised Isomap with Dissimilarity Measures in Embedding Learning, in Proc. of the Ibero-American Conference on Pattern Recognition, Progress in Pattern Recognition, Image Analysis and Applications, Lecture Notes in Computer Science (LNCS),Springer Berlin / Heidelberg, pp. 389-396, Vol. 5197, September 2008
  • S. Mukkamala, A. H. Sung, B. Ribeiro , A. S. Vieira, J. C. Neves, Model Selection and Feature Ranking for Financial Distress Classification. Proceedings of 8th International Conference on Enterprise Information Systems (ICEIS 2006), INSTICC - Institute for Systems and Technologies of Information, Control and Communication.
  • S. Mukkamala, G. D. Tilve, A. H. Sung, B. Ribeiro, A . S. Vieira (2006) Computational Intelligent Techniques for Financial Distress Detection. International Journal of Computational Intelligence Research (IJCIR) (2006), pp 60-65.
  • Bernardete Ribeiro, Armando Vieira and Joao Carvalho das Neves, Sparse Bayesian Models: Bankruptcy-Predictors of Choice?, 2006 International Joint Conference on Neural Networks, Vancouver, Canada.
  • Armando Vieira and Baldomero Oliva, Protein Loop Classification Using Artificial Neural Networks, Advances in Bioinformatics and Computational Biology, Proceedings of the Brazilian Simposium on Bioinformatics, pp. 222-225, João C. Setubal and Sergio Verjovski-Almeida Ed. (2005).
  • Armando Vieira, Bernardete Ribeiro and Joao C. Neves, A Method to Improve Generalization of Neural Networks: Application to the Problem of Bankruptcy Prediction, Proceeding ICANNGA-7, Springer Verlag series on Adaptative and Natural Computing Algorithms, 417 (2005)
  • Armando Vieira, An Iterative Artificial Neural Network for high dimensional data analysis, Artificial Neural Networks: Biological Inspirations - ICANN 2005: 15th International Conference, Warsaw, Poland, September 11-15, 2005. Proceedings II, Editors  W?odzis?aw Duch, Janusz Kacprzyk, Erkki Oja, et al., pp. 691-697 (2005).
  • S. Mukkamala, A. H. Sung, A. S. Vieira and J. C. Neves, Are Neural Networks The Best Predictors For Bankruptcy Detection?, The 12th International Conference on Neural Information Processing, Oct 30, Taipei, Taiwan (2005).
  • Armando Vieira, Bernardete Ribeiro and Joao C. Neves, A Method to Improve Generalization of Neural Networks: Application to the Problem of Bankruptcy Prediction, Proceeding ICANNGA-7, Springer Verlag series on Adaptative and Natural Computing Algorithms, 417 (2005).
  • A. Gaspar-Cunha, Armando S. Vieira, Multi-Objective Optimization: Hybridization of an Evolutionary Algorithm with Artificial Neural Networks for fast Convergence. Workshop on Design and Evaluation of Advanced Hybrid Meta-Heuristics, Nothingam, 3,4 November (2004).
  • A. Gaspar-Cunha e A. Vieira, A Multi-Objective Evolutionary Algorithm Using Neural Networks to Approximate Fitness Evaluations, International Journal of Computers, Systems and Signals, 231 (2004).
  • A. Gaspar-Cunha, A. S. Vieira, A Hybrid Multi-Objective Evolutionary Algorithm Using an Inverse Neural Network, HYBRID METAHEURISTICS (HM 2004) Workshop, Valencia, Spain, 178 (2004).
  • A. S. Vieira, B. Ribeiro, S. Mukkamala, J. C. Neves, A. H. Sung, On the Performance of Learning Machines for Bankruptcy Detection, IEEE International Conference on Computational Cybernetics, Vienna, Austria, August 30 - September 1, 223 - 227 (2004).
  • Gaspar-Cunha and A. Vieira, A Multi-Objective Evolutionary Algorithm Using Approximate Fitness Evaluations, European Conference on Applications of Genetic Algorithms EUROGEN 2003, p. 157, Barcelona 15-17 September (2003).
  • A. Vieira, Robust bankruptcy probability estimation using HLVQ, IWAMEM-03, International Workshop on Data Mining and Adaptative Modeling for Economics and Management, Porto, 15-16 September (2003).
  • A. Vieira, Application of HLVQ to bankruptcy prediction, ICMLA - International Conference of Machine Learning and Applications, pp. 327-332, Los Angeles (2003).
  • A. Vieira, P.A. Castillo and J. J. Merelo, Comparison of HLVQ and GProp in the problem of bankruptcy prediction, IWANN03 - International Workshop on Artificial Neural Networks, J. Mira (Ed.), pp. 655-662, LNCS 2687, Springer-Verlag, Menorca, Spain, June (2003).
  • V. Matias, G. Öhl, J.C. Soares, N. P. Barradas, A. Vieira, P.P. Freitas, S. Cardoso, Determination of the composition of light thin films with artificial neural networks analysis of Rutherford backscattering experiments Phys. Rev. E 67, article 046705 (2003).
  • G. Öhl, V. Matias, A. Vieira, N. P. Barradas, Artificial neural network analysis of RBS data with roughness: Application to Ti0.4Al0.6N/Mo multilayers, Nucl. Instrum. Methods B (2003).
  • A. Vieira and Nuno Barradas, A new training algorithm for classification of high dimensional data, Neurocomputing, 50C, 461-472 (2003).
  • A. Vieira, A new paradigm to teach physics to engineering students, mICTIE, International Conference on Technologies of  Information in Education, Badajoz (2003).
  • N. P. Barradas and A. Vieira, Artificial neural networks for automation of Rutherford backscattering spectroscopy experiments and data analysis, Phy. Rev. E, 65 66703 (2002).
  • A. Vieira, N. P. Barradas and E. Alves, Analysis of sapphire implanted with different elements using artificial neural networks, Nucl. Instr. Meth. B 190, 241 (2002).
  • N. P. Barradas, A. Vieira, R. Patrício, RBS Without Humans, Nucl. Instr. Meth. B,  190, 231-236 (2002).
  • A. Vieira, Why it is so difficult to predict social phenomena: a perspective from a physicist, CAUS - Conference of the SAS Users and Developers, Lisbon (2001).
  • J. A. Agapito, N. P. Barradas, F. M. Cardeira, J. Casas, A. P. Fernandes , F. J. Franco, P. Gomes, I. C. Goncalves, A. H. Cachero, J. Lozano, J. G. Marques, A. Paz, M. J. Prata, A. J. G. Ramalho, M. A. Rodríguez Ruiz, J. P. Santos and A. Vieira, Radiation Tests on Commercial Instrumentation Amplifiers, Analog Switches & DAC's, LEB2001, Sweden (2001).
  • A.Vieira, N. P. Barradas, Composition of Ni-Ta-C films using neural network analysis of Rutherford backscattering data, Nucl. Instr. Meth. B 174, 367-372 (2001).
  • A. Vieira, A. Fernandes, R. Patrício, Optimization of neutron beams for BNCT using artificial neural networks, Proceedings of the WSES International Conference on Neural Networks and Applications, p 34, Tenerife, 12-14 February (2001).
  • N. P. Barradas, A. Vieira and E. Alves, Artificial Neural Networks analysis of RBS data of Er-Implanted Sapphire, Nucl. Instr. Meth. B 175, 108 (2001).
  • A. Vieira, N. P. Barradas and C. Jeynes, Error performance analysis of Artificial Neural Networks applied to Rutherford backscattering data, Surf. Interface Anal., 31,35-38 (2001).
  • A. Vieira e N. Barradas, Artificial neural networks for analysis of Rutherford backscattering data, Phys. Rev. E 62, 5818 (2000).
  • A. Vieira, A. Ramalho, I. C. Gonçalves, A. Fernandes, N. Barradas, J. G. Marques,  J. Prata and C. Chaussy, Monte Carlo calculations for neutron and gamma radiation fields on a fast neutron irradiation device, Proceedings of International Conference "Monte Carlo 2000", Lisbon (2000).
  • A. Vieira, Democracy Online: framing a new political system based of the Internet, Proceedings of the International Conference on Public Participation and Information Technologies, Lisboa, 1999.
  • A. Ramalho, J. Marques, I. C. Goncalves, I. F. Goncalves, A. Fernandes, J. Prata and A. Vieira,  Use of RPI to test the behaviour under irradiation of electronic circuits and components for CERN, Proceedings of IAEA International Symposium on Research Reactor Utilization, Safety and Management, IAEA-SM-360, Lisboa (1999).
  • N. P. Barradas and A. Vieira, Artificial neural network algorithm for analysis of Rutherford backscattering data, Phys. Rev. E, 62, 5818 (2000).
  • A. Vieira and N. P. Barradas, Neural network analysis of Rutherford backscattering data, Nucl. Instr. Meth. B 170, 235 (2000).
  • A. Vieira and C. Guet, Fission of a charged liquid drop in an external electric field, European Journal of Physics D, in print.
  • F. F. Karpechine, A. Vieira, C. Fiolhais and J. da Providência Jr., On the ternary fission of atomic clusters, Europhysics Letters, 42, 149 (1998).
  • F. Nogueira, A. Vieira, M. Brajczewska and C. Fiolhais Charged metal clusters: atomistic versus continuous background descriptions, Proceedings of the 21st International Workshop, in Condensed Matter Theories, J. da Providência e F. B. Malik (Ed.), Vol XIII, Nova Science, New York, 1998, 333.
  • A. Vieira and C. Fiolhais Fission of Metallic Clusters within the Shell Correction Method, Proceedings of the International Symposium "Similarities and Differences Between Atomic Nuclei and Clusters", American Institute of Physics, ed. Y. Abe and S. M. Lee, 407 (1997).
  • A. Vieira and C. Fiolhais Shell correction effects on fission barrier of metallic clusters: a systematic description,  Phys. Rev. B 57, 7352 (1998).
  • A. Vieira, M. B. Torres, C. Fiolhais and L. C. Balbás, Comparison of the spherical averaged pseudopotential with the stabilized jellium model, J. Phys. B 30, 3583 (1997).
  • M. Brajczewska, A. Vieira, C. Fiolhais and J. P. Perdew, Volume shift and charge instability of simple-metal clusters, Progress in Surface Science, 53, 305 (1996).
  • A. Vieira, M. Brajczewska and C. Fiolhais, Self- expansion and compression of charged clusters of stabilized jellium, Int. J. Quantum Chem., 60, 1537 (1996).
  • A. Vieira and C. Fiolhais Fission of metallic clusters  in the liquid drop model, Phys. Lett. A 220, 231 (1996).
  • A. Vieira and C. Fiolhais The two-center shell model for the fission of metallic clusters, Z. Phys. D 37, 269  (1996).
  • C. Fiolhais and A. Vieira fission of Metallic clusters, in Collective Motions in Nuclear Dynamics Proceedings of the Predeal International Summer School, ed. A. Raduta, World Scientific, Singapore, p. 523 (1995).
  • A. Vieira and C. Fiolhais Decay of charged stabilized jellium clusters, Int. J. Quantum Chem., 56, 239 (1995).
  • Brajczewska, C. Fiolhais, A. Vieira and J. P. Perdew Self-compression of metallic clusters in the stabilized jellium model, Proceedings of "Many-Body Physics", eds. C. Fiolhais et al, World Scientific, Singapore, (1994).