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  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS GENÉTICOS

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      FERRANDIN, Mauri e CERRI, Ricardo. Ensemble multi-label classification using closed frequent labelsets and label taxonomies. Applied Soft Computing, v. 171, p. 1-12, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2025.112853. Acesso em: 28 nov. 2025.
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      Ferrandin, M., & Cerri, R. (2025). Ensemble multi-label classification using closed frequent labelsets and label taxonomies. Applied Soft Computing, 171, 1-12. doi:10.1016/j.asoc.2025.112853
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      Ferrandin M, Cerri R. Ensemble multi-label classification using closed frequent labelsets and label taxonomies [Internet]. Applied Soft Computing. 2025 ; 171 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.asoc.2025.112853
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      Ferrandin M, Cerri R. Ensemble multi-label classification using closed frequent labelsets and label taxonomies [Internet]. Applied Soft Computing. 2025 ; 171 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.asoc.2025.112853
  • Source: Health Information Science and Systems. Unidade: ICMC

    Subjects: SISTEMA DE SAÚDE, ALGORITMOS GENÉTICOS, TELEMEDICINA

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      PANG, Xinyu et al. Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm. Health Information Science and Systems, v. 11, p. 1-12, 2023Tradução . . Disponível em: https://doi.org/10.1007/s13755-023-00230-1. Acesso em: 28 nov. 2025.
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      Pang, X., Ge, Y. ‑F., Wang, K., Traina, A. J. M., & Wang, H. (2023). Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm. Health Information Science and Systems, 11, 1-12. doi:10.1007/s13755-023-00230-1
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      Pang X, Ge Y‑F, Wang K, Traina AJM, Wang H. Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm [Internet]. Health Information Science and Systems. 2023 ; 11 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s13755-023-00230-1
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      Pang X, Ge Y‑F, Wang K, Traina AJM, Wang H. Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm [Internet]. Health Information Science and Systems. 2023 ; 11 1-12.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s13755-023-00230-1
  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: ALGORITMOS GENÉTICOS, PROGRAMAÇÃO GENÉTICA, JOGOS DE COMPUTADOR

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      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: 28 nov. 2025.
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      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
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      Mariño JRH, Toledo CFM. Evolving interpretable strategies for zero-sum games [Internet]. Applied Soft Computing. 2022 ; 122 1-11.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.asoc.2022.108860
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      Mariño JRH, Toledo CFM. Evolving interpretable strategies for zero-sum games [Internet]. Applied Soft Computing. 2022 ; 122 1-11.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1016/j.asoc.2022.108860
  • Source: Applied Sciences. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA, HEURÍSTICA, ALGORITMOS GENÉTICOS

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      MATOS, Everton Alex et al. Pilot sequence allocation schemes in massive MIMO systems using heuristic approaches. Applied Sciences, v. 12, n. 10, p. 1-21, 2022Tradução . . Disponível em: https://doi.org/10.3390/app12105117. Acesso em: 28 nov. 2025.
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      Matos, E. A., Bonidia, R. P., Sanches, D. S., Pozza, R. S., & Sampaio, L. D. H. (2022). Pilot sequence allocation schemes in massive MIMO systems using heuristic approaches. Applied Sciences, 12( 10), 1-21. doi:10.3390/app12105117
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      Matos EA, Bonidia RP, Sanches DS, Pozza RS, Sampaio LDH. Pilot sequence allocation schemes in massive MIMO systems using heuristic approaches [Internet]. Applied Sciences. 2022 ; 12( 10): 1-21.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/app12105117
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      Matos EA, Bonidia RP, Sanches DS, Pozza RS, Sampaio LDH. Pilot sequence allocation schemes in massive MIMO systems using heuristic approaches [Internet]. Applied Sciences. 2022 ; 12( 10): 1-21.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/app12105117
  • Source: Sensors. Unidade: ICMC

    Subjects: ALGORITMOS GENÉTICOS, OTIMIZAÇÃO COMBINATÓRIA

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      VIANA, Monique Simplicio e CONTRERAS, Rodrigo Colnago e MORANDIN JUNIOR, Orides. A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem. Sensors, v. 22, p. 1-26, 2022Tradução . . Disponível em: https://doi.org/10.3390/s22124561. Acesso em: 28 nov. 2025.
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      Viana, M. S., Contreras, R. C., & Morandin Junior, O. (2022). A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem. Sensors, 22, 1-26. doi:10.3390/s22124561
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      Viana MS, Contreras RC, Morandin Junior O. A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem [Internet]. Sensors. 2022 ; 22 1-26.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/s22124561
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      Viana MS, Contreras RC, Morandin Junior O. A new frequency analysis operator for population improvement in genetic algorithms to solve the job shop scheduling problem [Internet]. Sensors. 2022 ; 22 1-26.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/s22124561
  • Source: Intelligent Information Management. Unidades: ICMC, EESC

    Subjects: ALGORITMOS GENÉTICOS, REDES NEURAIS, SISTEMAS EMBUTIDOS

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      ROSA, Nícolas dos Santos et al. Implementation on FPGA of neuro-genetic PID controllers auto-tuning. Intelligent Information Management, v. 14, n. 5, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.4236/iim.2022.145012. Acesso em: 28 nov. 2025.
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      Rosa, N. dos S., Arantes, M. da S., Toledo, C. F. M., & Lima, J. M. G. P. de B. (2022). Implementation on FPGA of neuro-genetic PID controllers auto-tuning. Intelligent Information Management, 14( 5), Se 2022. doi:10.4236/iim.2022.145012
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      Rosa N dos S, Arantes M da S, Toledo CFM, Lima JMGP de B. Implementation on FPGA of neuro-genetic PID controllers auto-tuning [Internet]. Intelligent Information Management. 2022 ; 14( 5): Se 2022.[citado 2025 nov. 28 ] Available from: https://doi.org/10.4236/iim.2022.145012
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      Rosa N dos S, Arantes M da S, Toledo CFM, Lima JMGP de B. Implementation on FPGA of neuro-genetic PID controllers auto-tuning [Internet]. Intelligent Information Management. 2022 ; 14( 5): Se 2022.[citado 2025 nov. 28 ] Available from: https://doi.org/10.4236/iim.2022.145012
  • Source: Evolutionary Intelligence. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS GENÉTICOS, RECONHECIMENTO DE PADRÕES

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      BASGALUPP, Márcio Porto et al. An extensive experimental evaluation of automated machine learning methods for recommending classification algorithms. Evolutionary Intelligence, v. 14, n. 4, p. 1895-1914, 2021Tradução . . Disponível em: https://doi.org/10.1007/s12065-020-00463-z. Acesso em: 28 nov. 2025.
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      Basgalupp, M. P., Barros, R. C., Sá, A. G. C. de, Pappa, G. L., Mantovani, R. G., Carvalho, A. C. P. de L. F. de, & Freitas, A. A. (2021). An extensive experimental evaluation of automated machine learning methods for recommending classification algorithms. Evolutionary Intelligence, 14( 4), 1895-1914. doi:10.1007/s12065-020-00463-z
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      Basgalupp MP, Barros RC, Sá AGC de, Pappa GL, Mantovani RG, Carvalho ACP de LF de, Freitas AA. An extensive experimental evaluation of automated machine learning methods for recommending classification algorithms [Internet]. Evolutionary Intelligence. 2021 ; 14( 4): 1895-1914.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s12065-020-00463-z
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      Basgalupp MP, Barros RC, Sá AGC de, Pappa GL, Mantovani RG, Carvalho ACP de LF de, Freitas AA. An extensive experimental evaluation of automated machine learning methods for recommending classification algorithms [Internet]. Evolutionary Intelligence. 2021 ; 14( 4): 1895-1914.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s12065-020-00463-z
  • Source: Earth Science Informatics. Unidade: ICMC

    Subjects: ESTUDO DE CASO, ALGORITMOS GENÉTICOS, RIOS, REGRESSÃO LINEAR

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      VIEIRA, Alen Costa et al. Improving flood forecasting through feature selection by a genetic algorithm: experiments based on real data from an Amazon rainforest river. Earth Science Informatics, v. 14, p. 37-50, 2021Tradução . . Disponível em: https://doi.org/10.1007/s12145-020-00528-8. Acesso em: 28 nov. 2025.
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      Vieira, A. C., Garcia, G., Pabón, R. E. C., Cota, L. P., Souza, P. de, Ueyama, J., & Pessin, G. (2021). Improving flood forecasting through feature selection by a genetic algorithm: experiments based on real data from an Amazon rainforest river. Earth Science Informatics, 14, 37-50. doi:10.1007/s12145-020-00528-8
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      Vieira AC, Garcia G, Pabón REC, Cota LP, Souza P de, Ueyama J, Pessin G. Improving flood forecasting through feature selection by a genetic algorithm: experiments based on real data from an Amazon rainforest river [Internet]. Earth Science Informatics. 2021 ; 14 37-50.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s12145-020-00528-8
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      Vieira AC, Garcia G, Pabón REC, Cota LP, Souza P de, Ueyama J, Pessin G. Improving flood forecasting through feature selection by a genetic algorithm: experiments based on real data from an Amazon rainforest river [Internet]. Earth Science Informatics. 2021 ; 14 37-50.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s12145-020-00528-8
  • Source: Evolutionary Intelligence. Unidade: EESC

    Subjects: ENGENHARIA AERONÁUTICA, AERONAVES NÃO TRIPULADAS, TRAJETÓRIA, ALGORITMOS GENÉTICOS

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      LIMA, Juliana Veiga Cardoso Fernandes de e BELO, Eduardo Morgado e MARQUES, Vinicius Abrão da Silva. Multi-agent path planning with nonlinear restrictions. Evolutionary Intelligence, p. [1-9], 2021Tradução . . Disponível em: https://doi.org/10.1007/s12065-020-00534-1. Acesso em: 28 nov. 2025.
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      Lima, J. V. C. F. de, Belo, E. M., & Marques, V. A. da S. (2021). Multi-agent path planning with nonlinear restrictions. Evolutionary Intelligence, [1-9]. doi:10.1007/s12065-020-00534-1
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      Lima JVCF de, Belo EM, Marques VA da S. Multi-agent path planning with nonlinear restrictions [Internet]. Evolutionary Intelligence. 2021 ; [1-9].[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s12065-020-00534-1
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      Lima JVCF de, Belo EM, Marques VA da S. Multi-agent path planning with nonlinear restrictions [Internet]. Evolutionary Intelligence. 2021 ; [1-9].[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s12065-020-00534-1
  • Source: Soft Computing. Unidade: ICMC

    Subjects: INTERAÇÃO USUÁRIO-COMPUTADOR, ESTADOS EMOCIONAIS, ALGORITMOS GENÉTICOS

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      MANO, Leandro Yukio et al. An intelligent and generic approach for detecting human emotions: a case study with facial expressions. Soft Computing, v. 24, p. 8467-8479, 2020Tradução . . Disponível em: https://doi.org/10.1007/s00500-019-04411-7. Acesso em: 28 nov. 2025.
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      Mano, L. Y., Faiçal, B. S., Gonçalves, V. P., Pessin, G., Gomes, P. H., Carvalho, A. C. P. de L. F. de, & Ueyama, J. (2020). An intelligent and generic approach for detecting human emotions: a case study with facial expressions. Soft Computing, 24, 8467-8479. doi:10.1007/s00500-019-04411-7
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      Mano LY, Faiçal BS, Gonçalves VP, Pessin G, Gomes PH, Carvalho ACP de LF de, Ueyama J. An intelligent and generic approach for detecting human emotions: a case study with facial expressions [Internet]. Soft Computing. 2020 ; 24 8467-8479.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s00500-019-04411-7
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      Mano LY, Faiçal BS, Gonçalves VP, Pessin G, Gomes PH, Carvalho ACP de LF de, Ueyama J. An intelligent and generic approach for detecting human emotions: a case study with facial expressions [Internet]. Soft Computing. 2020 ; 24 8467-8479.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1007/s00500-019-04411-7
  • Source: Sensors. Unidade: ICMC

    Subjects: ALGORITMOS GENÉTICOS, OTIMIZAÇÃO COMBINATÓRIA, SCHEDULING

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      VIANA, Monique Simplicio e MORANDIN JUNIOR, Orides e CONTRERAS, Rodrigo Colnago. A modified genetic algorithm with local search strategies and multi-crossover operator for Job Shop Scheduling Problem. Sensors, v. 20, n. 18, p. Se 2020, 2020Tradução . . Disponível em: https://doi.org/10.3390/s20185440. Acesso em: 28 nov. 2025.
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      Viana, M. S., Morandin Junior, O., & Contreras, R. C. (2020). A modified genetic algorithm with local search strategies and multi-crossover operator for Job Shop Scheduling Problem. Sensors, 20( 18), Se 2020. doi:10.3390/s20185440
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      Viana MS, Morandin Junior O, Contreras RC. A modified genetic algorithm with local search strategies and multi-crossover operator for Job Shop Scheduling Problem [Internet]. Sensors. 2020 ; 20( 18): Se 2020.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/s20185440
    • Vancouver

      Viana MS, Morandin Junior O, Contreras RC. A modified genetic algorithm with local search strategies and multi-crossover operator for Job Shop Scheduling Problem [Internet]. Sensors. 2020 ; 20( 18): Se 2020.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/s20185440
  • Source: Symmetry. Unidade: ICMC

    Subjects: ALGORITMOS GENÉTICOS, VISUALIZAÇÃO, HEURÍSTICA

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      VIANA, Monique Simplicio e MORANDIN JUNIOR, Orides e CONTRERAS, Rodrigo Colnago. An improved local search genetic algorithm with a new mapped adaptive operator applied to pseudo-coloring problem. Symmetry, v. 12, n. 10, p. 1-36, 2020Tradução . . Disponível em: https://doi.org/10.3390/sym12101684. Acesso em: 28 nov. 2025.
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      Viana, M. S., Morandin Junior, O., & Contreras, R. C. (2020). An improved local search genetic algorithm with a new mapped adaptive operator applied to pseudo-coloring problem. Symmetry, 12( 10), 1-36. doi:10.3390/sym12101684
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      Viana MS, Morandin Junior O, Contreras RC. An improved local search genetic algorithm with a new mapped adaptive operator applied to pseudo-coloring problem [Internet]. Symmetry. 2020 ; 12( 10): 1-36.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/sym12101684
    • Vancouver

      Viana MS, Morandin Junior O, Contreras RC. An improved local search genetic algorithm with a new mapped adaptive operator applied to pseudo-coloring problem [Internet]. Symmetry. 2020 ; 12( 10): 1-36.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/sym12101684
  • Source: Human Brain Mapping. Unidade: FM

    Subjects: LATERALIDADE, CÓRTEX PR-E-FRONTAL, MODELOS, TOMADA DE DECISÃO, HEMODINÂMICA, ALGORITMOS GENÉTICOS, ESTIMULAÇÃO NÃO LINEAR

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      BIAZOLI JR., Claudinei Eduardo et al. Nonlinear estimation of neural processing time from BOLD signal with application to decision-making. Human Brain Mapping, v. 33, n. 2, p. 334-348, 2012Tradução . . Disponível em: https://doi.org/10.1002/hbm.21214. Acesso em: 28 nov. 2025.
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      Biazoli Jr., C. E., Sato, J. R., Cardoso, E. F., Brammer, M. J., & Amaro Jr., E. (2012). Nonlinear estimation of neural processing time from BOLD signal with application to decision-making. Human Brain Mapping, 33( 2), 334-348. doi:10.1002/hbm.21214
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      Biazoli Jr. CE, Sato JR, Cardoso EF, Brammer MJ, Amaro Jr. E. Nonlinear estimation of neural processing time from BOLD signal with application to decision-making [Internet]. Human Brain Mapping. 2012 ; 33( 2): 334-348.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1002/hbm.21214
    • Vancouver

      Biazoli Jr. CE, Sato JR, Cardoso EF, Brammer MJ, Amaro Jr. E. Nonlinear estimation of neural processing time from BOLD signal with application to decision-making [Internet]. Human Brain Mapping. 2012 ; 33( 2): 334-348.[citado 2025 nov. 28 ] Available from: https://doi.org/10.1002/hbm.21214

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