Source: Journal of Petroleum Science and Engineering. Unidade: EP
Subjects: PERFURAÇÃO DE POÇOS, PETRÓLEO, REDES NEURAIS
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AGOSTINI, Cristiano Eduardo e PINTO, Marcio Augusto Sampaio. Probabilistic Neural Network with Bayesian-based, spectral torque imaging and Deep Convolutional Autoencoder for PDC bit wear monitoring. Journal of Petroleum Science and Engineering, v. 193, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.petrol.2020.1074342. Acesso em: 20 out. 2024.APA
Agostini, C. E., & Pinto, M. A. S. (2020). Probabilistic Neural Network with Bayesian-based, spectral torque imaging and Deep Convolutional Autoencoder for PDC bit wear monitoring. Journal of Petroleum Science and Engineering, 193. doi:10.1016/j.petrol.2020.1074342NLM
Agostini CE, Pinto MAS. Probabilistic Neural Network with Bayesian-based, spectral torque imaging and Deep Convolutional Autoencoder for PDC bit wear monitoring [Internet]. Journal of Petroleum Science and Engineering. 2020 ; 193[citado 2024 out. 20 ] Available from: https://doi.org/10.1016/j.petrol.2020.1074342Vancouver
Agostini CE, Pinto MAS. Probabilistic Neural Network with Bayesian-based, spectral torque imaging and Deep Convolutional Autoencoder for PDC bit wear monitoring [Internet]. Journal of Petroleum Science and Engineering. 2020 ; 193[citado 2024 out. 20 ] Available from: https://doi.org/10.1016/j.petrol.2020.1074342
