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Artigo de periodico
How have high-impact scientific studies designing their experiments on mixed data clustering? A systematic map to guide better choices (2021)
Martarelli, Nádia Junqueira; Nagano, Marcelo Seido
Source: Machine Learning with Applications. Unidade: EESC
Subjects: PESQUISA CIENTÍFICA, REVISÃO SISTEMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTARELLI, Nádia Junqueira e NAGANO, Marcelo Seido. How have high-impact scientific studies designing their experiments on mixed data clustering? A systematic map to guide better choices. Machine Learning with Applications, v. 5, p. Se 2021, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.mlwa.2021.100056. Acesso em: 17 out. 2024.
APA
Martarelli, N. J., & Nagano, M. S. (2021). How have high-impact scientific studies designing their experiments on mixed data clustering? A systematic map to guide better choices. Machine Learning with Applications, 5, Se 2021. doi:10.1016/j.mlwa.2021.100056
NLM
Martarelli NJ, Nagano MS. How have high-impact scientific studies designing their experiments on mixed data clustering? A systematic map to guide better choices [Internet]. Machine Learning with Applications. 2021 ; 5 Se 2021.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.mlwa.2021.100056
Vancouver
Martarelli NJ, Nagano MS. How have high-impact scientific studies designing their experiments on mixed data clustering? A systematic map to guide better choices [Internet]. Machine Learning with Applications. 2021 ; 5 Se 2021.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.mlwa.2021.100056
Artigo de periodico
Unsupervised feature selection based on bio-inspired approaches (2020)
Martarelli, Nádia Junqueira; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: ALGORITMOS GENÉTICOS, SIMULAÇÃO, TECNOLOGIA DA INFORMAÇÃO, MINERAÇÃO DE DADOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTARELLI, Nádia Junqueira e NAGANO, Marcelo Seido. Unsupervised feature selection based on bio-inspired approaches. Swarm and Evolutionary Computation, v. 52, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2019.100618. Acesso em: 17 out. 2024.
APA
Martarelli, N. J., & Nagano, M. S. (2020). Unsupervised feature selection based on bio-inspired approaches. Swarm and Evolutionary Computation, 52. doi:10.1016/j.swevo.2019.100618
NLM
Martarelli NJ, Nagano MS. Unsupervised feature selection based on bio-inspired approaches [Internet]. Swarm and Evolutionary Computation. 2020 ; 52[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2019.100618
Vancouver
Martarelli NJ, Nagano MS. Unsupervised feature selection based on bio-inspired approaches [Internet]. Swarm and Evolutionary Computation. 2020 ; 52[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2019.100618
Artigo de periodico
An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle (2019)
Tavares Neto, Roberto Fernandes; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: SCHEDULING, ALGORITMOS DE SCHEDULING, HEURÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TAVARES NETO, Roberto Fernandes e NAGANO, Marcelo Seido. An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle. Swarm and Evolutionary Computation, v. 44, p. 612-621, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2018.08.001. Acesso em: 17 out. 2024.
APA
Tavares Neto, R. F., & Nagano, M. S. (2019). An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle. Swarm and Evolutionary Computation, 44, 612-621. doi:10.1016/j.swevo.2018.08.001
NLM
Tavares Neto RF, Nagano MS. An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle [Internet]. Swarm and Evolutionary Computation. 2019 ; 44 612-621.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.08.001
Vancouver
Tavares Neto RF, Nagano MS. An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle [Internet]. Swarm and Evolutionary Computation. 2019 ; 44 612-621.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.08.001
Artigo de periodico
A constructive evolutionary approach for feature selection in unsupervised learning (2018)
Martarelli, Nádia Junqueira; Nagano, Marcelo Seido
Source: Swarm and Evolutionary Computation. Unidade: EESC
Subjects: ALGORITMOS GENÉTICOS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MARTARELLI, Nádia Junqueira e NAGANO, Marcelo Seido. A constructive evolutionary approach for feature selection in unsupervised learning. Swarm and Evolutionary Computation, v. 42, p. 125-137, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.swevo.2018.03.002. Acesso em: 17 out. 2024.
APA
Martarelli, N. J., & Nagano, M. S. (2018). A constructive evolutionary approach for feature selection in unsupervised learning. Swarm and Evolutionary Computation, 42, 125-137. doi:10.1016/j.swevo.2018.03.002
NLM
Martarelli NJ, Nagano MS. A constructive evolutionary approach for feature selection in unsupervised learning [Internet]. Swarm and Evolutionary Computation. 2018 ; 42 125-137.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.03.002
Vancouver
Martarelli NJ, Nagano MS. A constructive evolutionary approach for feature selection in unsupervised learning [Internet]. Swarm and Evolutionary Computation. 2018 ; 42 125-137.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.swevo.2018.03.002
Artigo de periodico
A closed-loop model of a multi-station and multi-product manufacturing system using bond graphs and hybrid controllers (2017)
Sagawa, Juliana Keiko; Nagano, Marcelo Seido ; Speranza Neto, Mauro
Source: European Journal of Operational Research. Unidade: EESC
Subjects: PLANEJAMENTO DA PRODUÇÃO, CONTROLE DA PRODUÇÃO, MANUFATURA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SAGAWA, Juliana Keiko e NAGANO, Marcelo Seido e SPERANZA NETO, Mauro. A closed-loop model of a multi-station and multi-product manufacturing system using bond graphs and hybrid controllers. European Journal of Operational Research, v. 258, n. 2, p. 677-691, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.ejor.2016.08.056. Acesso em: 17 out. 2024.
APA
Sagawa, J. K., Nagano, M. S., & Speranza Neto, M. (2017). A closed-loop model of a multi-station and multi-product manufacturing system using bond graphs and hybrid controllers. European Journal of Operational Research, 258( 2), 677-691. doi:10.1016/j.ejor.2016.08.056
NLM
Sagawa JK, Nagano MS, Speranza Neto M. A closed-loop model of a multi-station and multi-product manufacturing system using bond graphs and hybrid controllers [Internet]. European Journal of Operational Research. 2017 ; 258( 2): 677-691.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.ejor.2016.08.056
Vancouver
Sagawa JK, Nagano MS, Speranza Neto M. A closed-loop model of a multi-station and multi-product manufacturing system using bond graphs and hybrid controllers [Internet]. European Journal of Operational Research. 2017 ; 258( 2): 677-691.[citado 2024 out. 17 ] Available from: https://doi.org/10.1016/j.ejor.2016.08.056

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