Source: International Journal of Semantic Computing. Unidade: EESC
Subjects: PULVERIZADORES, MÁQUINAS AGRÍCOLAS, ENGENHARIA ELÉTRICA
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GAMBOA PEÑALOZA, Elmer Alexis et al. A model approach to infer the quality in agricultural sprayers supported by knowledge bases and experimental measurements. International Journal of Semantic Computing, v. 11, n. 3, p. 279-292, 2017Tradução . . Disponível em: https://doi.org/10.1142/S1793351X17400104. Acesso em: 04 jun. 2024.APA
Gamboa Peñaloza, E. A., Cruvinel, P. E., Oliveira, V. A. de, & Costa, A. G. F. (2017). A model approach to infer the quality in agricultural sprayers supported by knowledge bases and experimental measurements. International Journal of Semantic Computing, 11( 3), 279-292. doi:10.1142/S1793351X17400104NLM
Gamboa Peñaloza EA, Cruvinel PE, Oliveira VA de, Costa AGF. A model approach to infer the quality in agricultural sprayers supported by knowledge bases and experimental measurements [Internet]. International Journal of Semantic Computing. 2017 ; 11( 3): 279-292.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1142/S1793351X17400104Vancouver
Gamboa Peñaloza EA, Cruvinel PE, Oliveira VA de, Costa AGF. A model approach to infer the quality in agricultural sprayers supported by knowledge bases and experimental measurements [Internet]. International Journal of Semantic Computing. 2017 ; 11( 3): 279-292.[citado 2024 jun. 04 ] Available from: https://doi.org/10.1142/S1793351X17400104
