Hybrid simulated annealing and genetic algorithm for optimization of a rule-based algorithm for detection of gait events in impaired subjects (2020)
- Authors:
- USP affiliated authors: SIQUEIRA, ADRIANO ALMEIDA GONÇALVES - EESC ; TERRA, MARCO HENRIQUE - EESC ; IBARRA, JUAN CARLOS PEREZ - EESC
- Unidade: EESC
- DOI: 10.1109/AIM43001.2020.9158938
- Subjects: ROBÓTICA; SENSOR; INTELIGÊNCIA ARTIFICIAL
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
PÉREZ IBARRA, Juan Carlos et al. Hybrid simulated annealing and genetic algorithm for optimization of a rule-based algorithm for detection of gait events in impaired subjects. Proceedings. [s.l.]: IEEE/ASME. Disponível em: https://doi.org/10.1109/AIM43001.2020.9158938. Acesso em: 02 jan. 2026. , 2020 -
APA
Pérez Ibarra, J. C., Siqueira, A. A. G., Terra, M. H., & Krebs, H. I. (2020). Hybrid simulated annealing and genetic algorithm for optimization of a rule-based algorithm for detection of gait events in impaired subjects. Proceedings. [s.l.]: IEEE/ASME. doi:10.1109/AIM43001.2020.9158938 -
NLM
Pérez Ibarra JC, Siqueira AAG, Terra MH, Krebs HI. Hybrid simulated annealing and genetic algorithm for optimization of a rule-based algorithm for detection of gait events in impaired subjects [Internet]. Proceedings. 2020 ;[citado 2026 jan. 02 ] Available from: https://doi.org/10.1109/AIM43001.2020.9158938 -
Vancouver
Pérez Ibarra JC, Siqueira AAG, Terra MH, Krebs HI. Hybrid simulated annealing and genetic algorithm for optimization of a rule-based algorithm for detection of gait events in impaired subjects [Internet]. Proceedings. 2020 ;[citado 2026 jan. 02 ] Available from: https://doi.org/10.1109/AIM43001.2020.9158938 - Robust markovian impedance control applied to a modular knee-exoskeleton
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Informações sobre o DOI: 10.1109/AIM43001.2020.9158938 (Fonte: oaDOI API)
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