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Artigo de periodico
Using fuzzy clustering to address imprecision and uncertainty present in deterministic components of time series (2021)
Ferreira, Marcos Vinícius dos Santos; Rios, Ricardo Araújo ; Mello, Rodrigo Fernandes de ; Rios, Tatiane Nogueira
Source: Applied Soft Computing. Unidade: ICMC
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, FUZZY (INTELIGÊNCIA ARTIFICIAL)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERREIRA, Marcos Vinícius dos Santos et al. Using fuzzy clustering to address imprecision and uncertainty present in deterministic components of time series. Applied Soft Computing, v. 113, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2021.108011. Acesso em: 28 set. 2024.
APA
Ferreira, M. V. dos S., Rios, R. A., Mello, R. F. de, & Rios, T. N. (2021). Using fuzzy clustering to address imprecision and uncertainty present in deterministic components of time series. Applied Soft Computing, 113, 1-13. doi:10.1016/j.asoc.2021.108011
NLM
Ferreira MV dos S, Rios RA, Mello RF de, Rios TN. Using fuzzy clustering to address imprecision and uncertainty present in deterministic components of time series [Internet]. Applied Soft Computing. 2021 ; 113 1-13.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2021.108011
Vancouver
Ferreira MV dos S, Rios RA, Mello RF de, Rios TN. Using fuzzy clustering to address imprecision and uncertainty present in deterministic components of time series [Internet]. Applied Soft Computing. 2021 ; 113 1-13.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2021.108011
Artigo de periodico
Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections (2019)
Ponti, Moacir Antonelli ; Costa, Gabriel B. Paranhos da; Santos, Fernando Pereira dos ; Silveira, Kaue U
Source: Applied Soft Computing. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, ALGORITMOS PARA IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PONTI, Moacir Antonelli et al. Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections. Applied Soft Computing, v. 80, p. 414-424, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2019.04.013. Acesso em: 28 set. 2024.
APA
Ponti, M. A., Costa, G. B. P. da, Santos, F. P. dos, & Silveira, K. U. (2019). Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections. Applied Soft Computing, 80, 414-424. doi:10.1016/j.asoc.2019.04.013
NLM
Ponti MA, Costa GBP da, Santos FP dos, Silveira KU. Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections [Internet]. Applied Soft Computing. 2019 ; 80 414-424.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2019.04.013
Vancouver
Ponti MA, Costa GBP da, Santos FP dos, Silveira KU. Supervised and unsupervised relevance sampling in handcrafted and deep learning features obtained from image collections [Internet]. Applied Soft Computing. 2019 ; 80 414-424.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2019.04.013
Artigo de periodico
Inducing hierarchical multi-label classification rules with genetic algorithms (2019)
Cerri, Ricardo; Basgalupp, Márcio P; Barros, Rodrigo C; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Applied Soft Computing. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS GENÉTICOS, RECONHECIMENTO DE PADRÕES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CERRI, Ricardo et al. Inducing hierarchical multi-label classification rules with genetic algorithms. Applied Soft Computing, v. 77, p. 584-604, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2019.01.017. Acesso em: 28 set. 2024.
APA
Cerri, R., Basgalupp, M. P., Barros, R. C., & Carvalho, A. C. P. de L. F. de. (2019). Inducing hierarchical multi-label classification rules with genetic algorithms. Applied Soft Computing, 77, 584-604. doi:10.1016/j.asoc.2019.01.017
NLM
Cerri R, Basgalupp MP, Barros RC, Carvalho ACP de LF de. Inducing hierarchical multi-label classification rules with genetic algorithms [Internet]. Applied Soft Computing. 2019 ; 77 584-604.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2019.01.017
Vancouver
Cerri R, Basgalupp MP, Barros RC, Carvalho ACP de LF de. Inducing hierarchical multi-label classification rules with genetic algorithms [Internet]. Applied Soft Computing. 2019 ; 77 584-604.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2019.01.017
Artigo de periodico
Characterization of runtime resource usage from analysis of binary executable programs (2018)
Pinto, Renê de Souza; Delbem, Alexandre Cláudio Botazzo ; Monaco, Francisco José
Source: Applied Soft Computing. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, AVALIAÇÃO DE DESEMPENHO, GEOMETRIA E MODELAGEM COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PINTO, Renê de Souza e DELBEM, Alexandre Cláudio Botazzo e MONACO, Francisco José. Characterization of runtime resource usage from analysis of binary executable programs. Applied Soft Computing, v. 71, p. 1133-1152, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2017.12.040. Acesso em: 28 set. 2024.
APA
Pinto, R. de S., Delbem, A. C. B., & Monaco, F. J. (2018). Characterization of runtime resource usage from analysis of binary executable programs. Applied Soft Computing, 71, 1133-1152. doi:10.1016/j.asoc.2017.12.040
NLM
Pinto R de S, Delbem ACB, Monaco FJ. Characterization of runtime resource usage from analysis of binary executable programs [Internet]. Applied Soft Computing. 2018 ; 71 1133-1152.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2017.12.040
Vancouver
Pinto R de S, Delbem ACB, Monaco FJ. Characterization of runtime resource usage from analysis of binary executable programs [Internet]. Applied Soft Computing. 2018 ; 71 1133-1152.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2017.12.040
Artigo de periodico
Efficiency issues of evolutionary k-means (2011)
Naldi, Murilo Coelho; Campello, Ricardo José Gabrielli Barreto; Hruschka, Eduardo Raul ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Applied Soft Computing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NALDI, Murilo Coelho et al. Efficiency issues of evolutionary k-means. Applied Soft Computing, v. 11, n. 2, p. 1938-1952, 2011Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2010.06.010. Acesso em: 28 set. 2024.
APA
Naldi, M. C., Campello, R. J. G. B., Hruschka, E. R., & Carvalho, A. C. P. de L. F. de. (2011). Efficiency issues of evolutionary k-means. Applied Soft Computing, 11( 2), 1938-1952. doi:10.1016/j.asoc.2010.06.010
NLM
Naldi MC, Campello RJGB, Hruschka ER, Carvalho ACP de LF de. Efficiency issues of evolutionary k-means [Internet]. Applied Soft Computing. 2011 ; 11( 2): 1938-1952.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2010.06.010
Vancouver
Naldi MC, Campello RJGB, Hruschka ER, Carvalho ACP de LF de. Efficiency issues of evolutionary k-means [Internet]. Applied Soft Computing. 2011 ; 11( 2): 1938-1952.[citado 2024 set. 28 ] Available from: https://doi.org/10.1016/j.asoc.2010.06.010

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