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Artigo de periodico
RGCLI: robust graph that considers labeled instances for semi-supervised learning (2017)
Berton, Lilian; Faleiros, Thiago de Paulo; Valejo, Alan; Valverde-Rebaza, Jorge; Lopes, Alneu de Andrade
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BERTON, Lilian et al. RGCLI: robust graph that considers labeled instances for semi-supervised learning. Neurocomputing, v. 226, p. 238-248, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2016.11.053. Acesso em: 11 nov. 2025.
APA
Berton, L., Faleiros, T. de P., Valejo, A., Valverde-Rebaza, J., & Lopes, A. de A. (2017). RGCLI: robust graph that considers labeled instances for semi-supervised learning. Neurocomputing, 226, 238-248. doi:10.1016/j.neucom.2016.11.053
NLM
Berton L, Faleiros T de P, Valejo A, Valverde-Rebaza J, Lopes A de A. RGCLI: robust graph that considers labeled instances for semi-supervised learning [Internet]. Neurocomputing. 2017 ; 226 238-248.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2016.11.053
Vancouver
Berton L, Faleiros T de P, Valejo A, Valverde-Rebaza J, Lopes A de A. RGCLI: robust graph that considers labeled instances for semi-supervised learning [Internet]. Neurocomputing. 2017 ; 226 238-248.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2016.11.053
Artigo de periodico
Noise detection in the meta-learning level (2016)
Garcia, Luís P. F; Carvalho, André Carlos Ponce de Leon Ferreira de ; Lorena, Ana C
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GARCIA, Luís P. F e CARVALHO, André Carlos Ponce de Leon Ferreira de e LORENA, Ana C. Noise detection in the meta-learning level. Neurocomputing, v. 176, p. 14-25, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.12.100. Acesso em: 11 nov. 2025.
APA
Garcia, L. P. F., Carvalho, A. C. P. de L. F. de, & Lorena, A. C. (2016). Noise detection in the meta-learning level. Neurocomputing, 176, 14-25. doi:10.1016/j.neucom.2014.12.100
NLM
Garcia LPF, Carvalho ACP de LF de, Lorena AC. Noise detection in the meta-learning level [Internet]. Neurocomputing. 2016 ; 176 14-25.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.100
Vancouver
Garcia LPF, Carvalho ACP de LF de, Lorena AC. Noise detection in the meta-learning level [Internet]. Neurocomputing. 2016 ; 176 14-25.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.100
Artigo de periodico
Image quantization as a dimensionality reduction procedure in color and texture feature extraction (2016)
Ponti, Moacir Antonelli ; Nazaré, Tiago Santana de ; Thumé, Gabriela S
Source: Neurocomputing. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PONTI, Moacir Antonelli e NAZARÉ, Tiago Santana de e THUMÉ, Gabriela S. Image quantization as a dimensionality reduction procedure in color and texture feature extraction. Neurocomputing, v. 173, n. Ja 2016, p. 385-396, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.04.114. Acesso em: 11 nov. 2025.
APA
Ponti, M. A., Nazaré, T. S. de, & Thumé, G. S. (2016). Image quantization as a dimensionality reduction procedure in color and texture feature extraction. Neurocomputing, 173( Ja 2016), 385-396. doi:10.1016/j.neucom.2015.04.114
NLM
Ponti MA, Nazaré TS de, Thumé GS. Image quantization as a dimensionality reduction procedure in color and texture feature extraction [Internet]. Neurocomputing. 2016 ; 173( Ja 2016): 385-396.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.04.114
Vancouver
Ponti MA, Nazaré TS de, Thumé GS. Image quantization as a dimensionality reduction procedure in color and texture feature extraction [Internet]. Neurocomputing. 2016 ; 173( Ja 2016): 385-396.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.04.114
Artigo de periodico
PTS: Projected Topological Stream clustering algorithm (2016)
Pereira, Cássio M. M; Mello, Rodrigo Fernandes de
Source: Neurocomputing. Unidade: ICMC
Subjects: SISTEMAS DISTRIBUÍDOS, PROGRAMAÇÃO CONCORRENTE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PEREIRA, Cássio M. M e MELLO, Rodrigo Fernandes de. PTS: Projected Topological Stream clustering algorithm. Neurocomputing, v. 180, p. 16-26, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.08.094. Acesso em: 11 nov. 2025.
APA
Pereira, C. M. M., & Mello, R. F. de. (2016). PTS: Projected Topological Stream clustering algorithm. Neurocomputing, 180, 16-26. doi:10.1016/j.neucom.2015.08.094
NLM
Pereira CMM, Mello RF de. PTS: Projected Topological Stream clustering algorithm [Internet]. Neurocomputing. 2016 ; 180 16-26.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.08.094
Vancouver
Pereira CMM, Mello RF de. PTS: Projected Topological Stream clustering algorithm [Internet]. Neurocomputing. 2016 ; 180 16-26.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.08.094
Artigo de periodico
Automatic generation of LUTs for hardware neural networks (2016)
Dias, Maurício A.; Sales, Daniel O; Osório, Fernando Santos
Source: Neurocomputing. Unidade: ICMC
Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DIAS, Maurício A. e SALES, Daniel O e OSÓRIO, Fernando Santos. Automatic generation of LUTs for hardware neural networks. Neurocomputing, v. 180, p. 108-120, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.07.111. Acesso em: 11 nov. 2025.
APA
Dias, M. A., Sales, D. O., & Osório, F. S. (2016). Automatic generation of LUTs for hardware neural networks. Neurocomputing, 180, 108-120. doi:10.1016/j.neucom.2015.07.111
NLM
Dias MA, Sales DO, Osório FS. Automatic generation of LUTs for hardware neural networks [Internet]. Neurocomputing. 2016 ; 180 108-120.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.07.111
Vancouver
Dias MA, Sales DO, Osório FS. Automatic generation of LUTs for hardware neural networks [Internet]. Neurocomputing. 2016 ; 180 108-120.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.07.111
Artigo de periodico
An object-based visual selection framework (2016)
Benicasa, Alcides X; Quiles, Marcos G; Silva, Thiago C; Liang, Zhao; Romero, Roseli Aparecida Francelin
Source: Neurocomputing. Unidades: FFCLRP, ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, RECONHECIMENTO DE OBJETOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BENICASA, Alcides X et al. An object-based visual selection framework. Neurocomputing, v. 180, p. 35-54, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.10.111. Acesso em: 11 nov. 2025.
APA
Benicasa, A. X., Quiles, M. G., Silva, T. C., Liang, Z., & Romero, R. A. F. (2016). An object-based visual selection framework. Neurocomputing, 180, 35-54. doi:10.1016/j.neucom.2015.10.111
NLM
Benicasa AX, Quiles MG, Silva TC, Liang Z, Romero RAF. An object-based visual selection framework [Internet]. Neurocomputing. 2016 ; 180 35-54.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.10.111
Vancouver
Benicasa AX, Quiles MG, Silva TC, Liang Z, Romero RAF. An object-based visual selection framework [Internet]. Neurocomputing. 2016 ; 180 35-54.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.10.111
Artigo de periodico
A systematic review of multi-label feature selection and a new method based on label construction (2016)
Spolaôr, Newton; Monard, Maria Carolina ; Tsoumakas, Grigorios; Lee, Huei Diana
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton et al. A systematic review of multi-label feature selection and a new method based on label construction. Neurocomputing, v. 180, p. 3-15, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.07.118. Acesso em: 11 nov. 2025.
APA
Spolaôr, N., Monard, M. C., Tsoumakas, G., & Lee, H. D. (2016). A systematic review of multi-label feature selection and a new method based on label construction. Neurocomputing, 180, 3-15. doi:10.1016/j.neucom.2015.07.118
NLM
Spolaôr N, Monard MC, Tsoumakas G, Lee HD. A systematic review of multi-label feature selection and a new method based on label construction [Internet]. Neurocomputing. 2016 ; 180 3-15.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.07.118
Vancouver
Spolaôr N, Monard MC, Tsoumakas G, Lee HD. A systematic review of multi-label feature selection and a new method based on label construction [Internet]. Neurocomputing. 2016 ; 180 3-15.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2015.07.118
Artigo de periodico
Effect of label noise in the complexity of classification problems (2015)
Garcia, Luís P. F; Carvalho, André Carlos Ponce de Leon Ferreira de ; Lorena, Ana C
Source: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GARCIA, Luís P. F e CARVALHO, André Carlos Ponce de Leon Ferreira de e LORENA, Ana C. Effect of label noise in the complexity of classification problems. Neurocomputing, v. 160, p. 108-119, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.10.085. Acesso em: 11 nov. 2025.
APA
Garcia, L. P. F., Carvalho, A. C. P. de L. F. de, & Lorena, A. C. (2015). Effect of label noise in the complexity of classification problems. Neurocomputing, 160, 108-119. doi:10.1016/j.neucom.2014.10.085
NLM
Garcia LPF, Carvalho ACP de LF de, Lorena AC. Effect of label noise in the complexity of classification problems [Internet]. Neurocomputing. 2015 ; 160 108-119.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.10.085
Vancouver
Garcia LPF, Carvalho ACP de LF de, Lorena AC. Effect of label noise in the complexity of classification problems [Internet]. Neurocomputing. 2015 ; 160 108-119.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.10.085
Artigo de periodico
LoCH: a neighborhood-based multidimensional projection technique for high-dimensional sparse spaces (2015)
Fadel, Samuel G; Fatore, Francisco M; Duarte, Felipe S. L. G; Paulovich, Fernando Vieira
Source: Neurocomputing. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FADEL, Samuel G et al. LoCH: a neighborhood-based multidimensional projection technique for high-dimensional sparse spaces. Neurocomputing, v. fe 2015, p. 546-556, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.07.071. Acesso em: 11 nov. 2025.
APA
Fadel, S. G., Fatore, F. M., Duarte, F. S. L. G., & Paulovich, F. V. (2015). LoCH: a neighborhood-based multidimensional projection technique for high-dimensional sparse spaces. Neurocomputing, fe 2015, 546-556. doi:10.1016/j.neucom.2014.07.071
NLM
Fadel SG, Fatore FM, Duarte FSLG, Paulovich FV. LoCH: a neighborhood-based multidimensional projection technique for high-dimensional sparse spaces [Internet]. Neurocomputing. 2015 ; fe 2015 546-556.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.071
Vancouver
Fadel SG, Fatore FM, Duarte FSLG, Paulovich FV. LoCH: a neighborhood-based multidimensional projection technique for high-dimensional sparse spaces [Internet]. Neurocomputing. 2015 ; fe 2015 546-556.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.071
Artigo de periodico
Projection inspector: assessment and synthesis of multidimensional projections (2015)
Pagliosa, Paulo; Paulovich, Fernando Vieira ; Minghim, Rosane ; Levkowitz, Haim; Nonato, Luis Gustavo
Source: Neurocomputing. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, GEOMETRIA COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PAGLIOSA, Paulo et al. Projection inspector: assessment and synthesis of multidimensional projections. Neurocomputing, v. fe 2015, p. 599-610, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.07.072. Acesso em: 11 nov. 2025.
APA
Pagliosa, P., Paulovich, F. V., Minghim, R., Levkowitz, H., & Nonato, L. G. (2015). Projection inspector: assessment and synthesis of multidimensional projections. Neurocomputing, fe 2015, 599-610. doi:10.1016/j.neucom.2014.07.072
NLM
Pagliosa P, Paulovich FV, Minghim R, Levkowitz H, Nonato LG. Projection inspector: assessment and synthesis of multidimensional projections [Internet]. Neurocomputing. 2015 ; fe 2015 599-610.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.072
Vancouver
Pagliosa P, Paulovich FV, Minghim R, Levkowitz H, Nonato LG. Projection inspector: assessment and synthesis of multidimensional projections [Internet]. Neurocomputing. 2015 ; fe 2015 599-610.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.072
Artigo de periodico
Improving the kernel regularized least squares method for small-sample regression (2015)
Braga, Igor; Monard, Maria Carolina
Source: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRAGA, Igor e MONARD, Maria Carolina. Improving the kernel regularized least squares method for small-sample regression. Neurocomputing, v. 163, p. 106-114, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.12.097. Acesso em: 11 nov. 2025.
APA
Braga, I., & Monard, M. C. (2015). Improving the kernel regularized least squares method for small-sample regression. Neurocomputing, 163, 106-114. doi:10.1016/j.neucom.2014.12.097
NLM
Braga I, Monard MC. Improving the kernel regularized least squares method for small-sample regression [Internet]. Neurocomputing. 2015 ; 163 106-114.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.097
Vancouver
Braga I, Monard MC. Improving the kernel regularized least squares method for small-sample regression [Internet]. Neurocomputing. 2015 ; 163 106-114.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.097
Artigo de periodico
Graph-based measures to assist user assessment of multidimensional projections (2015)
Motta, Robson; Minghim, Rosane ; Lopes, Alneu de Andrade ; Oliveira, Maria Cristina Ferreira de
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MOTTA, Robson et al. Graph-based measures to assist user assessment of multidimensional projections. Neurocomputing, v. fe 2015, p. 583-598, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.09.063. Acesso em: 11 nov. 2025.
APA
Motta, R., Minghim, R., Lopes, A. de A., & Oliveira, M. C. F. de. (2015). Graph-based measures to assist user assessment of multidimensional projections. Neurocomputing, fe 2015, 583-598. doi:10.1016/j.neucom.2014.09.063
NLM
Motta R, Minghim R, Lopes A de A, Oliveira MCF de. Graph-based measures to assist user assessment of multidimensional projections [Internet]. Neurocomputing. 2015 ; fe 2015 583-598.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.09.063
Vancouver
Motta R, Minghim R, Lopes A de A, Oliveira MCF de. Graph-based measures to assist user assessment of multidimensional projections [Internet]. Neurocomputing. 2015 ; fe 2015 583-598.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.09.063
Artigo de periodico
A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets (2015)
Espezua, Soledad; Villanueva, Edwin; Maciel, Carlos Dias ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Neurocomputing. Unidades: EESC, ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, PROCESSAMENTO DE SINAIS, EXPRESSÃO GÊNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ESPEZUA, Soledad et al. A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets. Neurocomputing, v. fe 2015, p. 767-776, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.07.057. Acesso em: 11 nov. 2025.
APA
Espezua, S., Villanueva, E., Maciel, C. D., & Carvalho, A. C. P. de L. F. de. (2015). A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets. Neurocomputing, fe 2015, 767-776. doi:10.1016/j.neucom.2014.07.057
NLM
Espezua S, Villanueva E, Maciel CD, Carvalho ACP de LF de. A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets [Internet]. Neurocomputing. 2015 ; fe 2015 767-776.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.057
Vancouver
Espezua S, Villanueva E, Maciel CD, Carvalho ACP de LF de. A projection pursuit framework for supervised dimension reduction of high dimensional small sample datasets [Internet]. Neurocomputing. 2015 ; fe 2015 767-776.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.07.057
Artigo de periodico
A framework for bottom-up induction of oblique decision trees (2014)
Barros, Rodrigo C; Jaskowiak, Pablo A; Cerri, Ricardo; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARROS, Rodrigo C et al. A framework for bottom-up induction of oblique decision trees. Neurocomputing, v. 135, p. 3-12, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2013.01.067. Acesso em: 11 nov. 2025.
APA
Barros, R. C., Jaskowiak, P. A., Cerri, R., & Carvalho, A. C. P. de L. F. de. (2014). A framework for bottom-up induction of oblique decision trees. Neurocomputing, 135, 3-12. doi:10.1016/j.neucom.2013.01.067
NLM
Barros RC, Jaskowiak PA, Cerri R, Carvalho ACP de LF de. A framework for bottom-up induction of oblique decision trees [Internet]. Neurocomputing. 2014 ; 135 3-12.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2013.01.067
Vancouver
Barros RC, Jaskowiak PA, Cerri R, Carvalho ACP de LF de. A framework for bottom-up induction of oblique decision trees [Internet]. Neurocomputing. 2014 ; 135 3-12.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2013.01.067
Trabalho de evento-anais periodico
MetaStream: a meta-learning based method for periodic algorithm selection in time-changing data (2014)
Rossi, André Luis Debiaso; Carvalho, André Carlos Ponce de Leon Ferreira de ; Soares, Carlos; Souza, Bruno Feres de
Source: Neurocomputing. Conference titles: Brazilian Symposium on Neural Networks - SBRN. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ROSSI, André Luis Debiaso et al. MetaStream: a meta-learning based method for periodic algorithm selection in time-changing data. Neurocomputing. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.neucom.2013.05.048. Acesso em: 11 nov. 2025. , 2014
APA
Rossi, A. L. D., Carvalho, A. C. P. de L. F. de, Soares, C., & Souza, B. F. de. (2014). MetaStream: a meta-learning based method for periodic algorithm selection in time-changing data. Neurocomputing. Amsterdam: Elsevier. doi:10.1016/j.neucom.2013.05.048
NLM
Rossi ALD, Carvalho ACP de LF de, Soares C, Souza BF de. MetaStream: a meta-learning based method for periodic algorithm selection in time-changing data [Internet]. Neurocomputing. 2014 ; 127 52-64.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2013.05.048
Vancouver
Rossi ALD, Carvalho ACP de LF de, Soares C, Souza BF de. MetaStream: a meta-learning based method for periodic algorithm selection in time-changing data [Internet]. Neurocomputing. 2014 ; 127 52-64.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2013.05.048
Artigo de periodico
A hybrid meta-learning architecture for multi-objective optimization of SVM parameters (2014)
Miranda, Péricles B. C; Prudêncio, Ricardo B. C; Carvalho, André Carlos Ponce de Leon Ferreira de ; Soares, Carlos
Source: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MIRANDA, Péricles B. C et al. A hybrid meta-learning architecture for multi-objective optimization of SVM parameters. Neurocomputing, v. no 2014, p. 27-43, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.06.026. Acesso em: 11 nov. 2025.
APA
Miranda, P. B. C., Prudêncio, R. B. C., Carvalho, A. C. P. de L. F. de, & Soares, C. (2014). A hybrid meta-learning architecture for multi-objective optimization of SVM parameters. Neurocomputing, no 2014, 27-43. doi:10.1016/j.neucom.2014.06.026
NLM
Miranda PBC, Prudêncio RBC, Carvalho ACP de LF de, Soares C. A hybrid meta-learning architecture for multi-objective optimization of SVM parameters [Internet]. Neurocomputing. 2014 ; no 2014 27-43.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.06.026
Vancouver
Miranda PBC, Prudêncio RBC, Carvalho ACP de LF de, Soares C. A hybrid meta-learning architecture for multi-objective optimization of SVM parameters [Internet]. Neurocomputing. 2014 ; no 2014 27-43.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.06.026
Artigo de periodico
On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem (2014)
Martins, Jean P; Fonseca, Carlos M; Delbem, Alexandre Cláudio Botazzo
Source: Neurocomputing. Unidade: ICMC
Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTINS, Jean P e FONSECA, Carlos M e DELBEM, Alexandre Cláudio Botazzo. On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem. Neurocomputing, v. 146, p. 17-29, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.04.069. Acesso em: 11 nov. 2025.
APA
Martins, J. P., Fonseca, C. M., & Delbem, A. C. B. (2014). On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem. Neurocomputing, 146, 17-29. doi:10.1016/j.neucom.2014.04.069
NLM
Martins JP, Fonseca CM, Delbem ACB. On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem [Internet]. Neurocomputing. 2014 ; 146 17-29.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.04.069
Vancouver
Martins JP, Fonseca CM, Delbem ACB. On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem [Internet]. Neurocomputing. 2014 ; 146 17-29.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2014.04.069
Artigo de periodico
Combining meta-learning and search techniques to select parameters for support vector machines (2012)
Gomes, Taciana A. F.; Prudêncio, Ricardo B. C.; Soares, Carlos; Rossi, André L. D; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GOMES, Taciana A. F. et al. Combining meta-learning and search techniques to select parameters for support vector machines. Neurocomputing, v. 75, p. 3-13, 2012Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2011.07.005. Acesso em: 11 nov. 2025.
APA
Gomes, T. A. F., Prudêncio, R. B. C., Soares, C., Rossi, A. L. D., & Carvalho, A. C. P. de L. F. de. (2012). Combining meta-learning and search techniques to select parameters for support vector machines. Neurocomputing, 75, 3-13. doi:10.1016/j.neucom.2011.07.005
NLM
Gomes TAF, Prudêncio RBC, Soares C, Rossi ALD, Carvalho ACP de LF de. Combining meta-learning and search techniques to select parameters for support vector machines [Internet]. Neurocomputing. 2012 ; 75 3-13.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2011.07.005
Vancouver
Gomes TAF, Prudêncio RBC, Soares C, Rossi ALD, Carvalho ACP de LF de. Combining meta-learning and search techniques to select parameters for support vector machines [Internet]. Neurocomputing. 2012 ; 75 3-13.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2011.07.005
Artigo de periodico
Use of gene dependent mutation probability in evolutionary neural networks for non-stationary problems (2006)
Tinós, Renato; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Neurocomputing. Unidades: FFCLRP, ICMC
Assunto: ARQUITETURA E ORGANIZAÇÃO DE COMPUTADORES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TINÓS, Renato e CARVALHO, André Carlos Ponce de Leon Ferreira de. Use of gene dependent mutation probability in evolutionary neural networks for non-stationary problems. Neurocomputing, v. 70, n. 1-3, p. 44-54, 2006Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2006.07.005. Acesso em: 11 nov. 2025.
APA
Tinós, R., & Carvalho, A. C. P. de L. F. de. (2006). Use of gene dependent mutation probability in evolutionary neural networks for non-stationary problems. Neurocomputing, 70( 1-3), 44-54. doi:10.1016/j.neucom.2006.07.005
NLM
Tinós R, Carvalho ACP de LF de. Use of gene dependent mutation probability in evolutionary neural networks for non-stationary problems [Internet]. Neurocomputing. 2006 ; 70( 1-3): 44-54.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2006.07.005
Vancouver
Tinós R, Carvalho ACP de LF de. Use of gene dependent mutation probability in evolutionary neural networks for non-stationary problems [Internet]. Neurocomputing. 2006 ; 70( 1-3): 44-54.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.neucom.2006.07.005

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