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Artigo de periodico
Ensemble of classifiers based on multiobjective genetic sampling for imbalanced data (2020)
Fernandes, Everlandio Rebouças Queiroz ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Yao, Xin
Source: IEEE Transactions on Knowledge and Data Engineering. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, COMPUTAÇÃO EVOLUTIVA, ALGORITMOS GENÉTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FERNANDES, Everlandio Rebouças Queiroz e CARVALHO, André Carlos Ponce de Leon Ferreira de e YAO, Xin. Ensemble of classifiers based on multiobjective genetic sampling for imbalanced data. IEEE Transactions on Knowledge and Data Engineering, v. 32, n. 6, p. 1104-1115, 2020Tradução . . Disponível em: https://doi.org/10.1109/TKDE.2019.2898861. Acesso em: 10 nov. 2024.
APA
Fernandes, E. R. Q., Carvalho, A. C. P. de L. F. de, & Yao, X. (2020). Ensemble of classifiers based on multiobjective genetic sampling for imbalanced data. IEEE Transactions on Knowledge and Data Engineering, 32( 6), 1104-1115. doi:10.1109/TKDE.2019.2898861
NLM
Fernandes ERQ, Carvalho ACP de LF de, Yao X. Ensemble of classifiers based on multiobjective genetic sampling for imbalanced data [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2020 ; 32( 6): 1104-1115.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/TKDE.2019.2898861
Vancouver
Fernandes ERQ, Carvalho ACP de LF de, Yao X. Ensemble of classifiers based on multiobjective genetic sampling for imbalanced data [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2020 ; 32( 6): 1104-1115.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/TKDE.2019.2898861
Artigo de periodico
Evolutionary computing in recommender systems: a review of recent research (2017)
Horváth, Tomás; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Natural Computing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO EVOLUTIVA, ALGORITMOS GENÉTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HORVÁTH, Tomás e CARVALHO, André Carlos Ponce de Leon Ferreira de. Evolutionary computing in recommender systems: a review of recent research. Natural Computing, v. 16, n. 3, p. Se 2017, 2017Tradução . . Disponível em: https://doi.org/10.1007/s11047-016-9540-y. Acesso em: 10 nov. 2024.
APA
Horváth, T., & Carvalho, A. C. P. de L. F. de. (2017). Evolutionary computing in recommender systems: a review of recent research. Natural Computing, 16( 3), Se 2017. doi:10.1007/s11047-016-9540-y
NLM
Horváth T, Carvalho ACP de LF de. Evolutionary computing in recommender systems: a review of recent research [Internet]. Natural Computing. 2017 ; 16( 3): Se 2017.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/s11047-016-9540-y
Vancouver
Horváth T, Carvalho ACP de LF de. Evolutionary computing in recommender systems: a review of recent research [Internet]. Natural Computing. 2017 ; 16( 3): Se 2017.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/s11047-016-9540-y
Artigo de periodico
Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification (2015)
Barros, Rodrigo C; Basgalupp, Márcio P; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Genetic Programming and Evolvable Machines. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO EVOLUTIVA, ALGORITMOS GENÉTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARROS, Rodrigo C e BASGALUPP, Márcio P e CARVALHO, André Carlos Ponce de Leon Ferreira de. Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification. Genetic Programming and Evolvable Machines, v. 16, n. 3, p. Se 2015, 2015Tradução . . Disponível em: https://doi.org/10.1007/s10710-014-9235-z. Acesso em: 10 nov. 2024.
APA
Barros, R. C., Basgalupp, M. P., & Carvalho, A. C. P. de L. F. de. (2015). Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification. Genetic Programming and Evolvable Machines, 16( 3), Se 2015. doi:10.1007/s10710-014-9235-z
NLM
Barros RC, Basgalupp MP, Carvalho ACP de LF de. Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification [Internet]. Genetic Programming and Evolvable Machines. 2015 ; 16( 3): Se 2015.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/s10710-014-9235-z
Vancouver
Barros RC, Basgalupp MP, Carvalho ACP de LF de. Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification [Internet]. Genetic Programming and Evolvable Machines. 2015 ; 16( 3): Se 2015.[citado 2024 nov. 10 ] Available from: https://doi.org/10.1007/s10710-014-9235-z
Trabalho de evento
Using multi-objective artificial immune systems to find core collections based on molecular markers (2015)
Schlottfeldt, Shana; Walter, Maria Emilia M. T; Timmis, Jon; Carvalho, André Carlos Ponce de Leon Ferreira de ; Telles, Mariana P. C; Diniz Filho, José Alexandre F
Source: Proceedings. Conference titles: Genetic and Evolutionary Computation Conference - GECCO. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO EVOLUTIVA, ALGORITMOS GENÉTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SCHLOTTFELDT, Shana et al. Using multi-objective artificial immune systems to find core collections based on molecular markers. 2015, Anais.. New York: ACM, 2015. Disponível em: https://doi.org/10.1145/2739480.2754653. Acesso em: 10 nov. 2024.
APA
Schlottfeldt, S., Walter, M. E. M. T., Timmis, J., Carvalho, A. C. P. de L. F. de, Telles, M. P. C., & Diniz Filho, J. A. F. (2015). Using multi-objective artificial immune systems to find core collections based on molecular markers. In Proceedings. New York: ACM. doi:10.1145/2739480.2754653
NLM
Schlottfeldt S, Walter MEMT, Timmis J, Carvalho ACP de LF de, Telles MPC, Diniz Filho JAF. Using multi-objective artificial immune systems to find core collections based on molecular markers [Internet]. Proceedings. 2015 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2739480.2754653
Vancouver
Schlottfeldt S, Walter MEMT, Timmis J, Carvalho ACP de LF de, Telles MPC, Diniz Filho JAF. Using multi-objective artificial immune systems to find core collections based on molecular markers [Internet]. Proceedings. 2015 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1145/2739480.2754653
Trabalho de evento
Fine-tuning of UAV control rules for spraying pesticides on crop fields (2014)
Faiçal, Bruno S; Pessin, Gustavo; Filho, Geraldo P. R; Carvalho, André Carlos Ponce de Leon Ferreira de ; Furquim, Gustavo; Ueyama, Jó
Source: Proceedings. Conference titles: IEEE International Conference on Tools with Artificial Intelligence - ICTAI. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, COMPUTAÇÃO EVOLUTIVA, SISTEMAS DISTRIBUÍDOS, PROGRAMAÇÃO CONCORRENTE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FAIÇAL, Bruno S et al. Fine-tuning of UAV control rules for spraying pesticides on crop fields. 2014, Anais.. Los Alamitos: IEEE, 2014. Disponível em: https://doi.org/10.1109/ICTAI.2014.85. Acesso em: 10 nov. 2024.
APA
Faiçal, B. S., Pessin, G., Filho, G. P. R., Carvalho, A. C. P. de L. F. de, Furquim, G., & Ueyama, J. (2014). Fine-tuning of UAV control rules for spraying pesticides on crop fields. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICTAI.2014.85
NLM
Faiçal BS, Pessin G, Filho GPR, Carvalho ACP de LF de, Furquim G, Ueyama J. Fine-tuning of UAV control rules for spraying pesticides on crop fields [Internet]. Proceedings. 2014 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICTAI.2014.85
Vancouver
Faiçal BS, Pessin G, Filho GPR, Carvalho ACP de LF de, Furquim G, Ueyama J. Fine-tuning of UAV control rules for spraying pesticides on crop fields [Internet]. Proceedings. 2014 ;[citado 2024 nov. 10 ] Available from: https://doi.org/10.1109/ICTAI.2014.85

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