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Dupuis, A., Dadouchi, C., & Agard, B. (2023). A decision support system for sequencing production in the manufacturing industry. Computers & Industrial Engineering, 185, 109686 (14 pages). Lien externe
Dupuis, A., Dadouchi, C., & Agard, B. (2023). Methodology for multi-temporal prediction of crop rotations using recurrent neural networks. Smart Agricultural Technology, 4, 100152 (13 pages). Disponible
Dupuis, A., Dadouchi, C., & Agard, B. (2023). Performances of a Seq2Seq-LSTM methodology to predict crop rotations in Québec. Smart Agricultural Technology, 4, 100180 (12 pages). Disponible
Dupuis, A., Dadouchi, C., Agard, B., & Pellerin, R. (novembre 2022). Forecasting future product sequences to be processed in tire production using deep learning technique [Communication écrite]. International Conference on ENTERprise Information Systems (CENTERIS 2022), Lisbon, Portugal. Publié dans Procedia Computer Science, 219. Lien externe
Parrenin, L., Danjou, C., Agard, B., & Beauchemin, R. (2023). A decision support tool for the first stage of the tempering process of organic wheat grains in a mill. International Journal of Food Science and Technology, 58(10), 5478-5488. Disponible
Parrenin, L., Danjou, C., Agard, B., & Beauchemin, R. (2023). Future trends in organic flour milling: the role of AI. AIMS Agriculture and Food, 8(1), 48-77. Lien externe
Piat, J.-R., Danjou, C., Agard, B., & Beauchemin, R. (2023). A guideline to implement a CPS architecture in an SME. Production & Manufacturing Research, 11(1), 30 pages. Lien externe
