44 registros retornados

• Silva, A.J.,  Ludermir, T.B.,  de Oliveira, W.R..  Superposition Based Learning Algorithm.  1 - 6

• Pestov, V..  A Note on Sample Complexity of Learning Binary Output Neural Networks under Fixed Input Distributions.  7 - 12

• Jaskowiak, P.A.,  Campello, R.J.G.B,  Covoes, T.F,  Hruschka, E.R.  A Comparative Study on the Use of Correlation Coefficients for Redundant Feature Elimination.  13 - 18

• Santos, J.D.A.,  Barreto, G.A.,  Medeiros, C.M.S..  Estimating the Number of Hidden Neurons of the MLP Using Singular Value Decomposition and Principal Components Analysis: A Novel Approach.  19 - 24

• Heinen, M.R.;,  Engel, P.M.;.  IPNN: An Incremental Probabilistic Neural Network for Function Approximation and Regression Tasks.  25 - 30

• Correa, R.F.,  Pinheiro, B.F.;.  Self-Organizing Maps Applied to Information Retrieval of Dissertations and Theses from BDTD-UFPE.  31 - 36

• Kitani, E.C.,  Del Moral Hernandez, E.,  Thomaz, C.E.,  da Silva, L.A..  Visual Interpretation of Self Organizing Maps.  37 - 42

• Soares, G.E.,  Borges, H.E.,  Gomes, R.M.,  Oliveira, G.M.C..  Emergence of Neuronal Groups on a Self-Organized Spiking Neurons Network Based on Genetic Algorithm.  43 - 48

• Sakata, T.C.,  Faceli, K.,  de Souto, M.C.P.,  de Carvalho, A.C.P.L.F..  Improvements in the Partitions Selection Strategy for Set of Clustering Solutions.  49 - 54

• Canuto, A.M.P.,  Pintro, F.,  Neto, A.F.,  Fairhurst, M.C..  Enhancing Performance of Cancellable Fingerprint Biometrics Using Classifier Ensembles.  55 - 60

• Vale, K.O.,  Neto, A.F.,  Canuto, A.M.P.,  Dias, F.G..  Static and Dynamic Weights in Ensemble Systems Built by Class-Based Feature Selection Methods.  61 - 66

• Ribeiro, M.N.,  Prudencio, R.B.C..  Local Feature Selection for Generation of Ensembles in Text Clustering.  67 - 72

• Kanda, J.,  Carvalho, A.,  Hruschka, E.,  Soares, C.;.  Using Meta-learning to Classify Traveling Salesman Problems.  73 - 78

• Gomes, T.A.F.,  Prudencio, R.B.C.,  Soares, C.,  Rossi, A.L.D.,  Carvalho, A..  Combining Meta-learning and Search Techniques to SVM Parameter Selection.  79 - 84

• Lorena, A.C.,  Spolaor, N.,  Costa, I.G.,  Souto, M.C.P..  On the Complexity of Gene Marker Selection.  85 - 90

• Mendoza, M.R.,  Werhli, A.V..  Inferring Genetic Regulatory Networks with an Hierarchical Bayesian Model and a Parallel Sampling Algorithm.  91 - 96

• Araújo, B.,  Rodrigues, F.A.,  Silva, T.C.,  Liang Zhao.  Identifying Abnormal Nodes in Protein-Protein Interaction Networks.  97 - 102

• Benicasa, A.X.,  Romero, R.A.F..  Localization of Salient Objects in Scenes through Visual Attention.  103 - 108

• Ralha, C.G.,  Schneider, H.W.,  Walter, M.E.M.T.,  Cetertich Bazzan, A.L..  Reinforcement Learning Method for BioAgents.  109 - 114

• de Andrade, L.C.M.,  da Silva, I.N..  Very Short-Term Load Forecasting Using a Hybrid Neuro-fuzzy Approach.  115 - 120

• de Oliveira, M.M.F.,  Ebecken, N.F.F.,  de Oliveira, J.L.F.,  Nunes, L.M.P..  Artificial Neural Network for Predicting Extreme Sea Level Variation Associated with Severe Storms.  121 - 126

• Puma-Villanueva, W.J.,  Zuben, F.J.V..  Evolving Arbitrarily Connected Feedforward Neural Networks via Genetic Algorithms.  127 - 132

• Gomide, P.,  Milidiu, R.L..  Assessing Stock Market Time Series Predictors Quality through a Pairs Trading System.  133 - 139

• de Carvalho, A.B.,  Pozo, A..  The Control of Dominance Area in Particle Swarm Optimization Algorithms for Many-Objective Problems.  140 - 145

• Spolaor, N.,  Lorena, A.C.,  Lee, H.D..  Use of Multiobjective Genetic Algorithms in Feature Selection.  146 - 151

• de Campos, A.,  Pozo, A.T.R.,  Vergilio, S.R.,  Savegnago, T..  Many-Objective Evolutionary Algorithms in the Composition of Web Services.  152 - 157

• Bueno, M.L.P.,  Oliveira, G.M.B..  Algorithms to Augment Diversity and Convergence in Multiobjective Multicast Flow Routing.  158 - 163

• de Athayde Costa e Silva, M.,  dos Santos Coelho, L..  Biogeography-Based Optimization Combined with Predator-Prey Approach Applied to Economic Load Dispatch.  164 - 169

• da Cunha Brito, L.,  Macedo, C.J.A.,  Rocha, A.S.,  de Carvalho, P.H.P..  A Performance Analysis of Mono and Multi-objective Evolutionary Algorithms Assisted by Meta-modeling.  170 - 175

• Carabetti, E.G.,  de Souza, S.R.,  Fraga, M.C.P.,  Gama, P.H.A..  An Application of the Ant Colony System Metaheuristic to the Vehicle Routing Problem with Pickup and Delivery and Time Windows.  176 - 181

• Ciarelli, P.M.,  Salles, E.O.T.,  Oliveira, E..  An Evolving System Based on Probabilistic Neural Network.  182 - 187

• Cintra, M.E.,  Monard, M.C.,  de Arruda Camargo, H..  An Evaluation of Rule-Based Classification Models Induced by a Fuzzy Method and Two Classic Learning Algorithms.  188 - 193

• Pimenta, A.H.M.,  de Arruda Camargo, H..  Genetic Interval Type-2 Fuzzy Classifier Generation: A Comparative Approach.  194 - 199

• Valle, M.E..  A New Class of Implicative Fuzzy Associative Memories for the Reconstruction of Gray-Scale Images Corrupted by Salt and Pepper Noise.  200 - 205

• Rodrigues, M.C.,  de Araújo, F.M.U.,  Maitelli, A.L..  Multiple-Model Identification Using ANFIS for Nonlinear Systems.  206 - 211

• Diniz, A.A.R.,  Pires, P.R.M.,  de Melo, J.D.,  Neto, A.D.D.,  Filho, A.J.J.L.,  Kanazava, S.M..  Reinforcement Learning for Controlling a Coupled Tank System Based on the Scheduling of Different Controllers.  212 - 216

• Shimo, H.K.,  Roque, A.C.,  Tinós, R.,  Tejada, J.,  Morato, S..  Use of Evolutionary Robots as an Auxiliary Tool for Developing Behavioral Models of Rats in an Elevated Plus-Maze.  217 - 222

• Tinós, R.,  Shengxiang Yang.  Evolution Strategies with q-Gaussian Mutation for Dynamic Optimization Problems.  223 - 228

• Jeronymo, D.C.,  Borges, Y.C.C.,  dos S Coelho, L..  Clonal Selection Algorithm with Oppositional Approach Applied to Trajectory Planning of a Robotic Manipulator.  229 - 234

• Rosendo, M.,  Pozo, A..  Applying a Discrete Particle Swarm Optimization Algorithm to Combinatorial Problems.  235 - 240

• Cortes, O.A.C.,  da Silva, J.C..  A Local Search Algorithm Based on Clonal Selection and Genetic Mutation for Global Optimization.  241 - 246

• Valença, I.,  Ludermir, T.B.,  Valença, M..  Hybrid Systems to Select Variables for Time Series Forecasting Using MLP and Search Algorithms.  247 - 252

• Cerri, R.,  de Carvalho, A.C.P.L.F..  Hierarchical Multilabel Classification Using Top-Down Label Combination and Artificial Neural Networks.  253 - 258

• Silva, A.J.,  de Oliveira, W.R.,  Ludermir, T.B..  A Weightless Neural Node Based on a Probabilistic Quantum Memory.  259 - 264