Filtros : "Expert Systems with Applications" "REDES NEURAIS" Removido: "ENSINO E APRENDIZAGEM" Limpar

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  • Source: Expert Systems with Applications. Unidade: Interinstitucional de Pós-Graduação em Estatística

    Subjects: REDES NEURAIS, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), MERCADO FINANCEIRO

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      SOUTO, Hugo Gobato. Charting new avenues in financial forecasting with TimesNet: the impact of intraperiod and interperiod variations on realized volatility prediction. Expert Systems with Applications, v. 255, p. 1-22, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2024.124851. Acesso em: 19 nov. 2025.
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      Souto, H. G. (2024). Charting new avenues in financial forecasting with TimesNet: the impact of intraperiod and interperiod variations on realized volatility prediction. Expert Systems with Applications, 255, 1-22. doi:10.1016/j.eswa.2024.124851
    • NLM

      Souto HG. Charting new avenues in financial forecasting with TimesNet: the impact of intraperiod and interperiod variations on realized volatility prediction [Internet]. Expert Systems with Applications. 2024 ; 255 1-22.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2024.124851
    • Vancouver

      Souto HG. Charting new avenues in financial forecasting with TimesNet: the impact of intraperiod and interperiod variations on realized volatility prediction [Internet]. Expert Systems with Applications. 2024 ; 255 1-22.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2024.124851
  • Source: Expert Systems with Applications. Unidade: EP

    Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL

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      GLATT, Ruben et al. DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning. Expert Systems with Applications, v. 156, p. 113420, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2020.113420. Acesso em: 19 nov. 2025.
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      Glatt, R., Silva, F. L. da, Bianchi, R. A. da C., & Reali Costa, A. H. (2020). DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning. Expert Systems with Applications, 156, 113420. doi:10.1016/j.eswa.2020.113420
    • NLM

      Glatt R, Silva FL da, Bianchi RA da C, Reali Costa AH. DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning [Internet]. Expert Systems with Applications. 2020 ; 156 113420.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2020.113420
    • Vancouver

      Glatt R, Silva FL da, Bianchi RA da C, Reali Costa AH. DECAF: deep case-based policy inference for knowledge transfer in reinforcement learning [Internet]. Expert Systems with Applications. 2020 ; 156 113420.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2020.113420
  • Source: Expert Systems with Applications. Unidades: IFSC, ICMC

    Subjects: RECONHECIMENTO DE PADRÕES, REDES NEURAIS, PROCESSAMENTO DE IMAGENS

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      SÁ JUNIOR, Jarbas Joaci de Mesquita e RIBAS, Lucas Correia e BRUNO, Odemir Martinez. Randomized neural network based signature for dynamic texture classification. Expert Systems with Applications, v. No 2019, p. 194-200, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2019.05.055. Acesso em: 19 nov. 2025.
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      Sá Junior, J. J. de M., Ribas, L. C., & Bruno, O. M. (2019). Randomized neural network based signature for dynamic texture classification. Expert Systems with Applications, No 2019, 194-200. doi:10.1016/j.eswa.2019.05.055
    • NLM

      Sá Junior JJ de M, Ribas LC, Bruno OM. Randomized neural network based signature for dynamic texture classification [Internet]. Expert Systems with Applications. 2019 ; No 2019 194-200.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2019.05.055
    • Vancouver

      Sá Junior JJ de M, Ribas LC, Bruno OM. Randomized neural network based signature for dynamic texture classification [Internet]. Expert Systems with Applications. 2019 ; No 2019 194-200.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2019.05.055
  • Source: Expert Systems with Applications. Unidade: ICMC

    Subjects: ALGORITMOS GENÉTICOS, REDES NEURAIS, ANÁLISE DE DESEMPENHO

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      DENYSIUK, Roman e GASPAR-CUNHA, António e DELBEM, Alexandre Cláudio Botazzo. Neuroevolution for solving multiobjective knapsack problems. Expert Systems with Applications, v. 116, p. 65-77, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2018.09.004. Acesso em: 19 nov. 2025.
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      Denysiuk, R., Gaspar-Cunha, A., & Delbem, A. C. B. (2019). Neuroevolution for solving multiobjective knapsack problems. Expert Systems with Applications, 116, 65-77. doi:10.1016/j.eswa.2018.09.004
    • NLM

      Denysiuk R, Gaspar-Cunha A, Delbem ACB. Neuroevolution for solving multiobjective knapsack problems [Internet]. Expert Systems with Applications. 2019 ; 116 65-77.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2018.09.004
    • Vancouver

      Denysiuk R, Gaspar-Cunha A, Delbem ACB. Neuroevolution for solving multiobjective knapsack problems [Internet]. Expert Systems with Applications. 2019 ; 116 65-77.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2018.09.004
  • Source: Expert Systems with Applications. Unidade: ICMC

    Subjects: REDES NEURAIS, SISTEMAS DINÂMICOS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE OBJETOS

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      FERREIRA, Martha Dais et al. Designing architectures of convolutional neural networks to solve practical problems. Expert Systems with Applications, v. 94, p. 205-217, 2018Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2017.10.052. Acesso em: 19 nov. 2025.
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      Ferreira, M. D., Corrêa, D. C., Nonato, L. G., & Mello, R. F. de. (2018). Designing architectures of convolutional neural networks to solve practical problems. Expert Systems with Applications, 94, 205-217. doi:10.1016/j.eswa.2017.10.052
    • NLM

      Ferreira MD, Corrêa DC, Nonato LG, Mello RF de. Designing architectures of convolutional neural networks to solve practical problems [Internet]. Expert Systems with Applications. 2018 ; 94 205-217.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2017.10.052
    • Vancouver

      Ferreira MD, Corrêa DC, Nonato LG, Mello RF de. Designing architectures of convolutional neural networks to solve practical problems [Internet]. Expert Systems with Applications. 2018 ; 94 205-217.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2017.10.052
  • Source: Expert Systems with Applications. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM

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      AFFONSO, Carlos et al. Deep learning for biological image classification. Expert Systems with Applications, v. No 2017, p. 114-122, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2017.05.039. Acesso em: 19 nov. 2025.
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      Affonso, C., Rossi, A. L. D., Vieira, F. H. A., & Carvalho, A. C. P. de L. F. de. (2017). Deep learning for biological image classification. Expert Systems with Applications, No 2017, 114-122. doi:10.1016/j.eswa.2017.05.039
    • NLM

      Affonso C, Rossi ALD, Vieira FHA, Carvalho ACP de LF de. Deep learning for biological image classification [Internet]. Expert Systems with Applications. 2017 ; No 2017 114-122.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2017.05.039
    • Vancouver

      Affonso C, Rossi ALD, Vieira FHA, Carvalho ACP de LF de. Deep learning for biological image classification [Internet]. Expert Systems with Applications. 2017 ; No 2017 114-122.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2017.05.039
  • Source: Expert Systems with Applications. Unidade: FFCLRP

    Subjects: REDES NEURAIS, REDES COMPLEXAS, INTELIGÊNCIA ARTIFICIAL

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      BERTINI JUNIOR, João Roberto e NICOLETTI, Maria do Carmo e ZHAO, Liang. An embedded imputation method via Attribute-based Decision Graphs. Expert Systems with Applications, v. 57, p. 159-177, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2016.03.027. Acesso em: 19 nov. 2025.
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      Bertini Junior, J. R., Nicoletti, M. do C., & Zhao, L. (2016). An embedded imputation method via Attribute-based Decision Graphs. Expert Systems with Applications, 57, 159-177. doi:10.1016/j.eswa.2016.03.027
    • NLM

      Bertini Junior JR, Nicoletti M do C, Zhao L. An embedded imputation method via Attribute-based Decision Graphs [Internet]. Expert Systems with Applications. 2016 ; 57 159-177.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2016.03.027
    • Vancouver

      Bertini Junior JR, Nicoletti M do C, Zhao L. An embedded imputation method via Attribute-based Decision Graphs [Internet]. Expert Systems with Applications. 2016 ; 57 159-177.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1016/j.eswa.2016.03.027

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