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Artigo de periodico
PlantLncBoost: key features for plant ncRNA identification and significant improvement in accuracy and generalization (2025)
Tian, Xue‐Chan ; Nie, Shuai ; Domingues, Douglas ; Paschoal, Alexandre Rossi ; Jiang, Li‐Bo ; Mao, Jian‐Feng
Source: New Phytologist. Unidade: ESALQ
Subjects: ALGORITMOS GENÉTICOS, APRENDIZADO COMPUTACIONAL, MELHORAMENTO GENÉTICO VEGETAL, PLANTAS CULTIVADAS, REGULAÇÃO GÊNICA, RNA, SELEÇÃO GENÉTICA, TRANSFORMADA DE FOURIER
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TIAN, Xue‐Chan et al. PlantLncBoost: key features for plant ncRNA identification and significant improvement in accuracy and generalization. New Phytologist, v. 247, p. 1538–1549, 2025Tradução . . Disponível em: https://doi.org/10.1111/nph.70211. Acesso em: 27 nov. 2025.
APA
Tian, X. ‐C., Nie, S., Domingues, D., Paschoal, A. R., Jiang, L. ‐B., & Mao, J. ‐F. (2025). PlantLncBoost: key features for plant ncRNA identification and significant improvement in accuracy and generalization. New Phytologist, 247, 1538–1549. doi:10.1111/nph.70211
NLM
Tian X‐C, Nie S, Domingues D, Paschoal AR, Jiang L‐B, Mao J‐F. PlantLncBoost: key features for plant ncRNA identification and significant improvement in accuracy and generalization [Internet]. New Phytologist. 2025 ; 247 1538–1549.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1111/nph.70211
Vancouver
Tian X‐C, Nie S, Domingues D, Paschoal AR, Jiang L‐B, Mao J‐F. PlantLncBoost: key features for plant ncRNA identification and significant improvement in accuracy and generalization [Internet]. New Phytologist. 2025 ; 247 1538–1549.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1111/nph.70211
Artigo de periodico
Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm (2023)
Pang, Xinyu; Ge, Yong‑Feng ; Wang, Kate ; Traina, Agma Juci Machado ; Wang, Hua
Source: Health Information Science and Systems. Unidade: ICMC
Subjects: SISTEMA DE SAÚDE, ALGORITMOS GENÉTICOS, TELEMEDICINA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 27 nov. 2025.
APA
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
NLM
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. 27 ] Available from: https://doi.org/10.1007/s13755-023-00230-1
Vancouver
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. 27 ] Available from: https://doi.org/10.1007/s13755-023-00230-1
Artigo de periodico
Enhancing the sensor node localization algorithm based on improved DV-Hop and DE algorithms in wireless sensor networks (2020)
Han, Dezhi ; Yu, Yunping; Li, Kuan-Ching ; Mello, Rodrigo Fernandes de
Source: Sensors. Unidade: ICMC
Subjects: WIRELESS, ALGORITMOS GENÉTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HAN, Dezhi et al. Enhancing the sensor node localization algorithm based on improved DV-Hop and DE algorithms in wireless sensor networks. Sensors, v. 20, p. 1-24, 2020Tradução . . Disponível em: https://doi.org/10.3390/s20020343. Acesso em: 27 nov. 2025.
APA
Han, D., Yu, Y., Li, K. -C., & Mello, R. F. de. (2020). Enhancing the sensor node localization algorithm based on improved DV-Hop and DE algorithms in wireless sensor networks. Sensors, 20, 1-24. doi:10.3390/s20020343
NLM
Han D, Yu Y, Li K-C, Mello RF de. Enhancing the sensor node localization algorithm based on improved DV-Hop and DE algorithms in wireless sensor networks [Internet]. Sensors. 2020 ; 20 1-24.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/s20020343
Vancouver
Han D, Yu Y, Li K-C, Mello RF de. Enhancing the sensor node localization algorithm based on improved DV-Hop and DE algorithms in wireless sensor networks [Internet]. Sensors. 2020 ; 20 1-24.[citado 2025 nov. 27 ] Available from: https://doi.org/10.3390/s20020343
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: 27 nov. 2025.
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 2025 nov. 27 ] 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 2025 nov. 27 ] Available from: https://doi.org/10.1109/TKDE.2019.2898861

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