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Teresa Bernarda Ludermir: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir
    Using Machine Learning Techniques to Combine Forecasting Methods. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2004, pp:1122-1127 [Conf]
  2. Mêuser Jorge Silva Valença, Teresa Bernarda Ludermir, Anelle Valença
    River Flow Forecasting with Constructive Neural Network. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2005, pp:1031-1036 [Conf]
  3. Paulemir G. Campos, Teresa Bernarda Ludermir
    Literal and ProRulext: Algorithms for Rule Extraction of ANNs. [Citation Graph (0, 0)][DBLP]
    HIS, 2005, pp:143-148 [Conf]
  4. Amanda Pimentel e Silva Lins, Teresa Bernarda Ludermir
    Hybrid Optimization Algorithm for the Definition of MLP Neural Network Architectures and Weights. [Citation Graph (0, 0)][DBLP]
    HIS, 2005, pp:149-154 [Conf]
  5. Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir
    Selection of Models for Time Series Prediction via Meta-Learning. [Citation Graph (0, 0)][DBLP]
    HIS, 2002, pp:74-83 [Conf]
  6. Mêuser Jorge Silva Valença, Teresa Bernarda Ludermir, Anelle Valença
    River Flow Forecasting for Reservoir management through Neural Networks. [Citation Graph (0, 0)][DBLP]
    HIS, 2005, pp:545-547 [Conf]
  7. Mêuser Jorge Silva Valença, Teresa Bernarda Ludermir, Anelle Valença
    Modeling of the rainfall-runoff relationship with artificial neural network. [Citation Graph (0, 0)][DBLP]
    HIS, 2005, pp:548-550 [Conf]
  8. Patrícia Maforte dos Santos, Teresa Bernarda Ludermir, Ricardo Bastos Cavalcante Prudêncio
    Selection of Time Series Forecasting Models based on Performance Information. [Citation Graph (0, 0)][DBLP]
    HIS, 2004, pp:366-371 [Conf]
  9. Cleber Zanchettin, Teresa Bernarda Ludermir
    A Neuro-Fuzzy Model Applied to Odor Recognition in an Artificial Nose. [Citation Graph (0, 0)][DBLP]
    HIS, 2003, pp:917-926 [Conf]
  10. Cleber Zanchettin, Teresa Bernarda Ludermir
    Wavelet Filter for Noise Reduction and Signal Compression in an Artificial Nose. [Citation Graph (0, 0)][DBLP]
    HIS, 2003, pp:907-916 [Conf]
  11. Cleber Zanchettin, Ferdinand L. Minku, Teresa Bernarda Ludermir
    Design of Experiments in Neuro-Fuzzy Systems. [Citation Graph (0, 0)][DBLP]
    HIS, 2005, pp:218-226 [Conf]
  12. Leandro M. Almeida, Teresa Bernarda Ludermir
    A Hybrid Method for Searching Near-Optimal Artificial Neural Networks. [Citation Graph (0, 0)][DBLP]
    HIS, 2006, pp:36- [Conf]
  13. Marcio Carvalho, Teresa Bernarda Ludermir
    Particle Swarm Optimization of Feed-Forward Neural Networks with Weight Decay. [Citation Graph (0, 0)][DBLP]
    HIS, 2006, pp:5- [Conf]
  14. Alzennyr Da Silva, Francisco de A. T. de Carvalho, Teresa Bernarda Ludermir, Nicomedes Cavalcanti
    Comparing Metrics in Fuzzy Clustering for Symbolic Data on SODAS Format. [Citation Graph (0, 0)][DBLP]
    IBERAMIA, 2004, pp:727-736 [Conf]
  15. Aida A. Ferreira, Teresa Bernarda Ludermir, Ronaldo R. B. de Aquino
    Comparing Neural Network Architecture for Pattern Recognize System on Artificial Noses. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2005, pp:635-640 [Conf]
  16. Teresa Bernarda Ludermir, C. R. S. Lopes, A. B. Ludermir, Marcílio Carlos Pereira de Souto
    Neural Network Use for the Identification of Factors Related to Common Mental Disorders. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2005, pp:653-658 [Conf]
  17. Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir
    Selecting and Ranking Time Series Models Using the NOEMON Approach. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:654-661 [Conf]
  18. Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir
    A Machine Learning Approach to Define Weights for Linear Combination of Forecasts. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2006, pp:274-283 [Conf]
  19. Ricardo Bezerra de Andrade e Silva, Teresa Bernarda Ludermir
    Obtaining Simplified Rule Bases by Hybrid Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:879-886 [Conf]
  20. Marcio Carvalho, Teresa Bernarda Ludermir
    Hybrid Training of Feed-Forward Neural Networks with Particle Swarm Optimization. [Citation Graph (0, 0)][DBLP]
    ICONIP (2), 2006, pp:1061-1070 [Conf]
  21. Renato Fernandes Corrêa, Teresa Bernarda Ludermir
    Web Documents Categorization Using Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:758-762 [Conf]
  22. Renato Fernandes Corrêa, Teresa Bernarda Ludermir
    Dimensionality Reduction by Semantic Mapping in Text Categorization. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:1032-1037 [Conf]
  23. Gecynalda Soares S. Gomes, Teresa Bernarda Ludermir
    Feature Selection for Neural Networks Through Binomial Regression. [Citation Graph (0, 0)][DBLP]
    ICONIP (2), 2006, pp:737-745 [Conf]
  24. André Luis S. Maia, Francisco de A. T. de Carvalho, Teresa Bernarda Ludermir
    A Hybrid Model for Symbolic Interval Time Series Forecasting. [Citation Graph (0, 0)][DBLP]
    ICONIP (2), 2006, pp:934-941 [Conf]
  25. Amanda Pimentel e Silva Lins, Teresa Bernarda Ludermir
    A Neighbor Generation Mechanism Optimizing Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:613-618 [Conf]
  26. Fernanda L. Minku, Teresa Bernarda Ludermir
    EFuNN Ensembles Construction Using a Clustering Method and a Coevolutionary Multi-objective Genetic Algorithm. [Citation Graph (0, 0)][DBLP]
    ICONIP (3), 2006, pp:884-891 [Conf]
  27. Teresa Bernarda Ludermir, Wilson Rosa de Oliveira
    Extracting Rules from Boolean Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:1666-1669 [Conf]
  28. Mêuser Jorge Silva Valença, Teresa Bernarda Ludermir
    Hydrological Forecasting and Updating Procedures for Neural Network. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:1304-1309 [Conf]
  29. Cleber Zanchettin, Teresa Bernarda Ludermir
    Evolving Fuzzy Neural Networks Applied to Odor Recognition. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:953-958 [Conf]
  30. Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Marcília A. Campos
    Encoding of Probabilistic Automata into RAM-Based Neural Networks. [Citation Graph (0, 0)][DBLP]
    IJCNN (3), 2000, pp:439-444 [Conf]
  31. Cleber Zanchettin, Teresa Bernarda Ludermir
    Hybrid Technique for Artificial Neural Network Architecture and Weight Optimization. [Citation Graph (0, 0)][DBLP]
    PKDD, 2005, pp:709-716 [Conf]
  32. Estefane G. M. de Lacerda, André Carlos Ponce Leon Ferreira de Carvalho, Teresa Bernarda Ludermir
    A Study of Crossvalidation and Bootstrap as Objective Functions for Genetic Algorithms. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:118-123 [Conf]
  33. Maria Silva Santos Barbosa, Teresa Bernarda Ludermir, Marizete Silva Santos, Francisco Luiz dos Santos, José Edison Gomes de Souza, Celso Pinto de Melo
    Pattern recognition of gases of petroleum based on RBF model. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:111- [Conf]
  34. Estefane G. M. de Lacerda, Teresa Bernarda Ludermir, André Carlos Ponce Leon Ferreira de Carvalho
    Evolutionary Optimization of RBF Networks. [Citation Graph (0, 0)][DBLP]
    SBRN, 2000, pp:219-224 [Conf]
  35. C. R. S. Lopes, Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto, A. B. Ludermir
    Neural Networks for the analysis of Common Mental Disorders Factors. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:114- [Conf]
  36. Teresa Bernarda Ludermir
    Extracting Rules from Feedforward Boolean Neural Networks. [Citation Graph (0, 0)][DBLP]
    SBRN, 1998, pp:61-66 [Conf]
  37. Eleonora Ma. Jesus Oliveira, Teresa Bernarda Ludermir
    Forecasting the IBOVESPA Using NARX Networks and Random Walk Model . [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:115-117 [Conf]
  38. Wilson Rosa de Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir
    Turing Machines with Finite Memory. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:67-73 [Conf]
  39. Renato Fernandes Corrêa, Teresa Bernarda Ludermir
    Automatic Text Categorization: Case Study. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:150- [Conf]
  40. José Carlos Martins Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir
    Implementation of Probabilistic Automata in Weightless Neural Networks. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:235- [Conf]
  41. Jairo Diniz Filho, Teresa Bernarda Ludermir
    Modulatory Interaction as a Support to Modeling Neural Substrates of the Decision Process. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:242- [Conf]
  42. Domingos Vanderlei Filho, Marcos A. dos Santos, Teresa Bernarda Ludermir, Mêuser Jorge Silva Valença
    A Fuzzy Approach to Support a Musculoskeletal Disorders Diagnosis. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:154-155 [Conf]
  43. Mêuser Jorge Silva Valença, Teresa Bernarda Ludermir
    Monthly Streamflow Forecasting Using an Neural Fuzzy Network Model. [Citation Graph (0, 0)][DBLP]
    SBRN, 2000, pp:117-119 [Conf]
  44. Mêuser Jorge Silva Valença, Teresa Bernarda Ludermir
    NeuroInflow: The New Model to Forecast Average Monthly Inflow. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:74-79 [Conf]
  45. Mêuser Jorge Silva Valença, Teresa Bernarda Ludermir
    Self-Organizing Modeling in Forecasting Daily River Flows. [Citation Graph (0, 0)][DBLP]
    SBRN, 1998, pp:210-214 [Conf]
  46. Akio Yamazaki, Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto
    Global Optimization Methods for Designing and Training Neural Networks. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:136-141 [Conf]
  47. Estefane G. M. de Lacerda, André Carlos Ponce Leon Ferreira de Carvalho, Antônio de Pádua Braga, Teresa Bernarda Ludermir
    Evolutionary Radial Basis Functions for Credit Assessment. [Citation Graph (0, 0)][DBLP]
    Appl. Intell., 2005, v:22, n:3, pp:167-181 [Journal]
  48. Cleber Zanchettin, Teresa Bernarda Ludermir
    Wavelet filter for noise reduction and signal compression in an artificial nose. [Citation Graph (0, 0)][DBLP]
    Appl. Soft Comput., 2007, v:7, n:1, pp:246-256 [Journal]
  49. Ricardo Bezerra de Andrade e Silva, Teresa Bernarda Ludermir
    Hybrid systems of local basis functions. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2001, v:5, n:3, pp:227-244 [Journal]
  50. Antônio de Pádua Braga, Teresa Bernarda Ludermir
    Editorial: "Artificial Neural Networks in Brazil: An Introduction to the Special Issue of IJNS". [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1999, v:9, n:3, pp:163-165 [Journal]
  51. Jairo Diniz Filho, Teresa Bernarda Ludermir
    Modeling a Particular Decision Process by Using a Modulatory Activation Function. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2003, v:13, n:2, pp:111-118 [Journal]
  52. Estefane G. M. de Lacerda, André Carlos Ponce Leon Ferreira de Carvalho, Teresa Bernarda Ludermir
    Evolutionary Optimization of RBF Networks. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2001, v:11, n:3, pp:287-294 [Journal]
  53. C. Nobre, E. Martineli, Antônio de Pádua Braga, André Carlos Ponce de Leon Ferreira de Carvalho, S. Rezende, José L. Braga, Teresa Bernarda Ludermir
    Knowledge Extraction: A Comparison between Symbolic and Connectionist Methods. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1999, v:9, n:3, pp:257-264 [Journal]
  54. Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto
    Introduction by Guest Editors. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2003, v:13, n:2, pp:55-57 [Journal]
  55. Marcílio Carlos Pereira de Souto, Paulo J. L. Adeodato, Teresa Bernarda Ludermir
    Sequential RAM-based Neural Networks: Learnability, Generalisation, Knowledge Extraction, and Grammatical Inference. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1999, v:9, n:3, pp:203-210 [Journal]
  56. Akio Yamazaki, Teresa Bernarda Ludermir
    Neural Network Training with Global Optimization Techniques. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2003, v:13, n:2, pp:77-86 [Journal]
  57. Cleber Zanchettin, Teresa Bernarda Ludermir
    Hybrid neural systems for pattern recognition in artificial noses. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2005, v:15, n:1-2, pp:137-149 [Journal]
  58. Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir
    Meta-learning approaches to selecting time series models. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2004, v:61, n:, pp:121-137 [Journal]
  59. Renato Fernandes Corrêa, Teresa Bernarda Ludermir
    Improving self-organization of document collections by semantic mapping. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:70, n:1-3, pp:62-69 [Journal]
  60. Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto
    The VIIth Brazilian Symposium on Neural Networks (SBRN'02). [Citation Graph (0, 0)][DBLP]
    Journal of Intelligent and Fuzzy Systems, 2002, v:13, n:2-4, pp:61-62 [Journal]
  61. Wilson Rosa de Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir
    Turing's analysis of computation and artificial neural networks. [Citation Graph (0, 0)][DBLP]
    Journal of Intelligent and Fuzzy Systems, 2002, v:13, n:2-4, pp:85-98 [Journal]
  62. Estefane G. M. de Lacerda, André Carlos Ponce Leon Ferreira de Carvalho, Teresa Bernarda Ludermir
    Model selection via Genetic Algorithms for RBF networks. [Citation Graph (0, 0)][DBLP]
    Journal of Intelligent and Fuzzy Systems, 2002, v:13, n:2-4, pp:111-122 [Journal]
  63. Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir, Francisco de A. T. de Carvalho
    A Modal Symbolic Classifier for selecting time series models. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2004, v:25, n:8, pp:911-921 [Journal]
  64. Estefane G. M. de Lacerda, André Carlos Ponce Leon Ferreira de Carvalho, Teresa Bernarda Ludermir
    Um Tutorial sobre Algoritmos Genéticos. [Citation Graph (0, 0)][DBLP]
    RITA, 2002, v:9, n:3, pp:7-39 [Journal]
  65. Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir
    Active Learning to Support the Generation of Meta-examples. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:817-826 [Conf]
  66. Fernanda L. Minku, Teresa Bernarda Ludermir
    Evolutionary strategies and genetic algorithms for dynamic parameter optimization of evolving fuzzy neural networks. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:1951-1958 [Conf]

  67. Automatically searching near-optimal artificial neural networks. [Citation Graph (, )][DBLP]


  68. Active Selection of Training Examples for Meta-Learning. [Citation Graph (, )][DBLP]


  69. Application of a Hybrid Classifier to the Recognition of Petrochemical Odors. [Citation Graph (, )][DBLP]


  70. Particle Swarm Optimization of Neural Network Architectures andWeights. [Citation Graph (, )][DBLP]


  71. Complementary Log-Log and Probit: Activation Functions Implemented in Artificial Neural Networks. [Citation Graph (, )][DBLP]


  72. Tuning Artificial Neural Networks Parameters Using an Evolutionary Algorithm. [Citation Graph (, )][DBLP]


  73. Using Reservoir Computing for Forecasting Time Series: Brazilian Case Study. [Citation Graph (, )][DBLP]


  74. Improved Semantic Mapping and SOM Applied to Document Organization. [Citation Graph (, )][DBLP]


  75. Predicting the Performance of Learning Algorithms Using Support Vector Machines as Meta-regressors. [Citation Graph (, )][DBLP]


  76. Active Generation of Training Examples in Meta-Regression. [Citation Graph (, )][DBLP]


  77. A Two Stage Clustering Method Combining Self-Organizing Maps and Ant K-Means. [Citation Graph (, )][DBLP]


  78. An Analysis of Meta-learning Techniques for Ranking Clustering Algorithms Applied to Artificial Data. [Citation Graph (, )][DBLP]


  79. Hybrid Systems for River Flood Forecasting Using MLP, SOM and Fuzzy Systems. [Citation Graph (, )][DBLP]


  80. Hybrid Optimization Technique for Artificial Neural Networks Design. [Citation Graph (, )][DBLP]


  81. Comparison of the Effectiveness of Different Cost Functions in Global Optimization Techniques. [Citation Graph (, )][DBLP]


  82. Analysis of mammogram using self-organizing neural networks based on spatial isomorphism. [Citation Graph (, )][DBLP]


  83. Hybrid model with dynamic architecture for forecasting time series. [Citation Graph (, )][DBLP]


  84. A methodology to train and improve artificial neural networks' weights and connections. [Citation Graph (, )][DBLP]


  85. Evolving both size and accuracy of RBF networks using Memetic Algorithm. [Citation Graph (, )][DBLP]


  86. An evolutionary approach for the clustering data problem. [Citation Graph (, )][DBLP]


  87. Feature subset selection in a methodology for training and improving artificial neural network weights and connections. [Citation Graph (, )][DBLP]


  88. Ranking and selecting clustering algorithms using a meta-learning approach. [Citation Graph (, )][DBLP]


  89. Active Meta-Learning with Uncertainty Sampling and Outlier Detection. [Citation Graph (, )][DBLP]


  90. Comparative study on normalization procedures for cluster analysis of gene expression datasets. [Citation Graph (, )][DBLP]


  91. An improved method for automatically searching near-optimal artificial Neural Networks. [Citation Graph (, )][DBLP]


  92. Investigating the use of Reservoir Computing for forecasting the hourly wind speed in short -term. [Citation Graph (, )][DBLP]


  93. Optimization of Neural Networks Weights and Architecture: A Multimodal Methodology. [Citation Graph (, )][DBLP]


  94. Combining Uncertainty Sampling Methods for Active Meta-Learning. [Citation Graph (, )][DBLP]


  95. Semantic mapping and K-means applied to hybrid SOM-based document organization system construction. [Citation Graph (, )][DBLP]


  96. Symbolic interval time series forecasting using a hybrid model. [Citation Graph (, )][DBLP]


  97. Weightless Neural Networks: Knowledge-Based Inference System. [Citation Graph (, )][DBLP]


  98. Selecting Neural Network Forecasting Models Using the Zoomed-Ranking Approach. [Citation Graph (, )][DBLP]


  99. Quantum Logical Neural Networks. [Citation Graph (, )][DBLP]


  100. Using Support Vector Machines to Predict the Performance of MLP Neural Networks. [Citation Graph (, )][DBLP]


  101. The Influence of Different Cost Functions in Global Optimization Techniques. [Citation Graph (, )][DBLP]


  102. EFuNN Ensembles Construction Using CONE with Multi-objective GA. [Citation Graph (, )][DBLP]


  103. An Analysis Of PSO Hybrid Algorithms For Feed-Forward Neural Networks Training. [Citation Graph (, )][DBLP]


  104. A Hybrid SOM-Based Document Organization System. [Citation Graph (, )][DBLP]


  105. LearningWeights for Linear Combination of Forecasting Methods. [Citation Graph (, )][DBLP]


  106. An Evolutionary Approach for Tuning Artificial Neural Network Parameters. [Citation Graph (, )][DBLP]


  107. Clustering cancer gene expression data: a comparative study. [Citation Graph (, )][DBLP]


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