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Alejo, L., Atkinson, J., Guzman-Fierro, V., & Roeckel, M. (2018). Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques. Environ. Sci. Pollut. Res., 25(21), 21149–21163.
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Brems, A., Caceres, G., Dewil, R., Baeyens, J., & Pitie, E. (2013). Heat transfer to the riser-wall of a circulating fluidised bed (CFB). Energy, 50, 493–500.
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Chang, M., Liu, B., Wang, B., Martinez-Villalobos, C., Ren, G., & Zhou, T. (2022). Understanding future increases in precipitation extremes in global land monsoon regions. J. Clim., 35, 1839–1851.
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Concha-Vega, P., Goles, E., Montealegre, P., & Rios-Wilson, M. (2022). On the Complexity of Stable and Biased Majority. Mathematics, 10(18), 3408.
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Goles, E., & Montealegre, P. (2020). The complexity of the asynchronous prediction of the majority automata. Inf. Comput., 274(SI).
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Goles, E., Montealegre, P., & Rios-Wilson, M. (2020). On The Effects Of Firing Memory In The Dynamics Of Conjunctive Networks. Discret. Contin. Dyn. Syst., 40(10), 5765–5793.
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Goles, E., Montealegre, P., Salo, V., & Torma, I. (2016). PSPACE-completeness of majority automata networks. Theor. Comput. Sci., 609, 118–128.
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Ruiz, E., Yushimito, W. F., Aburto, L., & de la Cruz, R. (2024). Predicting passenger satisfaction in public transportation using machine learning models. Transp. Res. A Policy Pract., 181, 103995.
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Simon, F., Ordonez, J., Reddy, T. A., Girard, A., & Muneer, T. (2016). Developing multiple regression models from the manufacturer's ground-source heat pump catalogue data. Renew. Energy, 95, 413–421.
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Vera, R., Araya, R., Garin, C., Ossandon, S., & Rojas, P. (2019). Study on the effect of atmospheric corrosion on mechanical properties with impact test: Carbon steel and Galvanized steel. Mater. Corros., 70(7), 1151–1161.
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