Filtros : "Applied Soft Computing" "Toledo, Claudio Fabiano Motta" Limpar

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  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: ALGORITMOS GENÉTICOS, PROGRAMAÇÃO GENÉTICA, JOGOS DE COMPUTADOR

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    • ABNT

      MARIÑO, Julian Ricardo Hernandez e TOLEDO, Claudio Fabiano Motta. Evolving interpretable strategies for zero-sum games. Applied Soft Computing, v. 122, p. 1-11, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2022.108860. Acesso em: 11 nov. 2025.
    • APA

      Mariño, J. R. H., & Toledo, C. F. M. (2022). Evolving interpretable strategies for zero-sum games. Applied Soft Computing, 122, 1-11. doi:10.1016/j.asoc.2022.108860
    • NLM

      Mariño JRH, Toledo CFM. Evolving interpretable strategies for zero-sum games [Internet]. Applied Soft Computing. 2022 ; 122 1-11.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2022.108860
    • Vancouver

      Mariño JRH, Toledo CFM. Evolving interpretable strategies for zero-sum games [Internet]. Applied Soft Computing. 2022 ; 122 1-11.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2022.108860
  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: JOGOS DE COMPUTADOR, OTIMIZAÇÃO RESTRITA, ALGORITMOS GENÉTICOS

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    • ABNT

      VIANA, Breno Mauricio de Freitas et al. Feasible-infeasible two-population genetic algorithm to evolve dungeon levels with dependencies in barrier mechanics. Applied Soft Computing, v. 119, p. 1-16, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2022.108586. Acesso em: 11 nov. 2025.
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      Viana, B. M. de F., Pereira, L. T., Toledo, C. F. M., Santos, S. R. dos, & Maia, S. M. D. M. (2022). Feasible-infeasible two-population genetic algorithm to evolve dungeon levels with dependencies in barrier mechanics. Applied Soft Computing, 119, 1-16. doi:10.1016/j.asoc.2022.108586
    • NLM

      Viana BM de F, Pereira LT, Toledo CFM, Santos SR dos, Maia SMDM. Feasible-infeasible two-population genetic algorithm to evolve dungeon levels with dependencies in barrier mechanics [Internet]. Applied Soft Computing. 2022 ; 119 1-16.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2022.108586
    • Vancouver

      Viana BM de F, Pereira LT, Toledo CFM, Santos SR dos, Maia SMDM. Feasible-infeasible two-population genetic algorithm to evolve dungeon levels with dependencies in barrier mechanics [Internet]. Applied Soft Computing. 2022 ; 119 1-16.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2022.108586
  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA

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    • ABNT

      ROSA, L. S et al. Design and analysis of evolutionary bit-length optimization algorithms for floating to fixed-point conversion. Applied Soft Computing, v. 49, p. 447-461, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2016.08.035. Acesso em: 11 nov. 2025.
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      Rosa, L. S., Delbem, A. C. B., Toledo, C. F. M., & Bonato, V. (2016). Design and analysis of evolutionary bit-length optimization algorithms for floating to fixed-point conversion. Applied Soft Computing, 49, 447-461. doi:10.1016/j.asoc.2016.08.035
    • NLM

      Rosa LS, Delbem ACB, Toledo CFM, Bonato V. Design and analysis of evolutionary bit-length optimization algorithms for floating to fixed-point conversion [Internet]. Applied Soft Computing. 2016 ; 49 447-461.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2016.08.035
    • Vancouver

      Rosa LS, Delbem ACB, Toledo CFM, Bonato V. Design and analysis of evolutionary bit-length optimization algorithms for floating to fixed-point conversion [Internet]. Applied Soft Computing. 2016 ; 49 447-461.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2016.08.035
  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA

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    • ABNT

      PAIVA, Jonatas Lopes de e TOLEDO, Claudio Fabiano Motta e PEDRINI, Hélio. An approach based on hybrid genetic algorithm applied to image denoising problem. Applied Soft Computing, v. 46, p. 778-791, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2015.09.013. Acesso em: 11 nov. 2025.
    • APA

      Paiva, J. L. de, Toledo, C. F. M., & Pedrini, H. (2016). An approach based on hybrid genetic algorithm applied to image denoising problem. Applied Soft Computing, 46, 778-791. doi:10.1016/j.asoc.2015.09.013
    • NLM

      Paiva JL de, Toledo CFM, Pedrini H. An approach based on hybrid genetic algorithm applied to image denoising problem [Internet]. Applied Soft Computing. 2016 ; 46 778-791.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2015.09.013
    • Vancouver

      Paiva JL de, Toledo CFM, Pedrini H. An approach based on hybrid genetic algorithm applied to image denoising problem [Internet]. Applied Soft Computing. 2016 ; 46 778-791.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2015.09.013
  • Source: Applied Soft Computing. Unidade: ICMC

    Assunto: OTIMIZAÇÃO

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      TOLEDO, Claudio Fabiano Motta et al. Glass container production scheduling through hybrid multi-population based evolutionary algorithm. Applied Soft Computing, v. 13, n. 3, p. 1352\20131364, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2012.03.074. Acesso em: 11 nov. 2025.
    • APA

      Toledo, C. F. M., Arantes, M. da S., Oliveira, R. R. R. de, & Almada-Lobo, B. (2013). Glass container production scheduling through hybrid multi-population based evolutionary algorithm. Applied Soft Computing, 13( 3), 1352\20131364. doi:10.1016/j.asoc.2012.03.074
    • NLM

      Toledo CFM, Arantes M da S, Oliveira RRR de, Almada-Lobo B. Glass container production scheduling through hybrid multi-population based evolutionary algorithm [Internet]. Applied Soft Computing. 2013 ; 13( 3): 1352\20131364.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2012.03.074
    • Vancouver

      Toledo CFM, Arantes M da S, Oliveira RRR de, Almada-Lobo B. Glass container production scheduling through hybrid multi-population based evolutionary algorithm [Internet]. Applied Soft Computing. 2013 ; 13( 3): 1352\20131364.[citado 2025 nov. 11 ] Available from: https://doi.org/10.1016/j.asoc.2012.03.074

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