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Filtros : "SEP" "APRENDIZADO COMPUTACIONAL" Removido: "Goularte, Rudinei" Limpar

Filtros

Tese (Doutorado)
Simulations and serious games for the transition towards Industry 4.0: an action research on the development of serious virtual game in an academic environment (2022)
Chaim, Omar Cheidde; Cazarini, Edson Walmir (Orientador)
Unidade: EESC
Subjects: JOGOS, INDÚSTRIA 4.0, DESENVOLVIMENTO PROFISSIONAL, APRENDIZADO COMPUTACIONAL, APRENDIZAGEM, CAPACITAÇÃO TECNOLÓGICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHAIM, Omar Cheidde. Simulations and serious games for the transition towards Industry 4.0: an action research on the development of serious virtual game in an academic environment. 2022. Tese (Doutorado) – Universidade de São Paulo, São Carlos, 2022. Disponível em: https://www.teses.usp.br/teses/disponiveis/18/18157/tde-10102022-162533/. Acesso em: 16 ago. 2024.
APA
Chaim, O. C. (2022). Simulations and serious games for the transition towards Industry 4.0: an action research on the development of serious virtual game in an academic environment (Tese (Doutorado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/18/18157/tde-10102022-162533/
NLM
Chaim OC. Simulations and serious games for the transition towards Industry 4.0: an action research on the development of serious virtual game in an academic environment [Internet]. 2022 ;[citado 2024 ago. 16 ] Available from: https://www.teses.usp.br/teses/disponiveis/18/18157/tde-10102022-162533/
Vancouver
Chaim OC. Simulations and serious games for the transition towards Industry 4.0: an action research on the development of serious virtual game in an academic environment [Internet]. 2022 ;[citado 2024 ago. 16 ] Available from: https://www.teses.usp.br/teses/disponiveis/18/18157/tde-10102022-162533/
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: 16 ago. 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 ago. 16 ] 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 ago. 16 ] Available from: https://doi.org/10.1016/j.swevo.2018.03.002

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