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Articles

Computational modeling of biodiesel production using supercritical methanol

Pages 14-20 | Received 01 Jun 2017, Accepted 16 Jun 2017, Published online: 05 Oct 2018

References

  • Andrade, J. E., Perez, A., Sebastian, P. J., and Eapen, D. 2011. Retracted: A review of bio-diesel production processes. Biomass and Bioenergy 35:1008–1020. doi:10.1016/j.biombioe.2010.12.037.
  • Baghban, A. 2016. Application of the ANFIS strategy to estimate vaporization enthalpies of petroleum fractions and pure hydrocarbons. Petroleum Science and Technology 34:1359–1366. doi:10.1080/10916466.2016.1202975.
  • Baghban, A., Abbasi, P., and Rostami, P. 2016a. Modeling of viscosity for mixtures of Athabasca bitumen and heavy n-alkane with LSSVM algorithm. Petroleum Science and Technology 34:1698–1704. doi:10.1080/10916466.2016.1219748.
  • Baghban, A., Abbasi, P., Rostami, P., Bahadori, M., Ahmad, Z., Kashiwao, T., and Bahadori, A. 2016b. Estimation of oil and gas properties in petroleum production and processing operations using rigorous model. Petroleum Science and Technology 34:1129–1136. doi:10.1080/10916466.2016.1183028.bk_AQCmts7b
  • Baghban, A., Ahmadi, M. A., Pouladi, B., and Amanna, B. 2015a. Phase equilibrium modeling of semi-clathrate hydrates of seven commonly gases in the presence of TBAB ionic liquid promoter based on a low parameter connectionist technique. The Journal of Supercritical Fluids 101:184–192. doi:10.1016/j.supflu.2015.03.004.bk_AQCmts8b
  • Baghban, A., Ahmadi, M. A., and Shahraki, B. H. 2015b. Prediction carbon dioxide solubility in presence of various ionic liquids using computational intelligence approaches. The Journal of Supercritical Fluids 98:50–64. doi:10.1016/j.supflu.2015.01.002.
  • Baghban, A., Bahadori, A., Mohammadi, A. H., and Behbahaninia, A. 2017a. Prediction of CO2 loading capacities of aqueous solutions of absorbents using different computational schemes. International Journal of Greenhouse Gas Control 57:143–161. doi:10.1016/j.ijggc.2016.12.010.bk_AQCmts9b
  • Baghban, A., Bahadori, M., Ahmad, Z., Kashiwao, T., and Bahadori, A. 2016c. Modeling of true vapor pressure of petroleum products using ANFIS algorithm. Petroleum Science and Technology 34:933–939. doi:10.1080/10916466.2016.1170843.
  • Baghban, A., Bahadori, M., Lemraski, A. S., and Bahadori, A. 2016d. Prediction of solubility of ammonia in liquid electrolytes using least square support vector machines. Ain Shams Engineering Journal. doi:10.1016/j.asej.2016.08.006.
  • Baghban, A., Bahadori, M., Rozyn, J., Lee, M., Abbas, A., Bahadori, A., and Rahimali, A. 2016e. Estimation of air dew point temperature using computational intelligence schemes. Applied Thermal Engineering 93:1043–1052. doi:10.1016/j.applthermaleng.2015.10.056.
  • Baghban, A., and Khoshkharam, A. 2016. Application of LSSVM strategy to estimate asphaltene precipitation during different production processes. Petroleum Science and Technology 34:1855–1860. doi:10.1080/10916466.2016.1237966.
  • Baghban, A., Mohammadi, A. H., and Taleghani, M. S. 2017b. Rigorous modeling of CO2 equilibrium absorption in ionic liquids. International Journal of Greenhouse Gas Control 58:19–41. doi:10.1016/j.ijggc.2016.12.009.
  • Cortes, C., and Vapnik, V. 1995. Support-vector networks. Machine Learning 20:273–297. doi:10.1007/BF00994018.
  • Farobie, O., Hasanah, N., and Matsumura, Y. 2015. Artificial neural network modeling to predict biodiesel production in supercritical methanol and ethanol using spiral reactor. Procedia Environmental Sciences 28:214–223. doi:10.1016/j.proenv.2015.07.028.
  • Leung, D. Y. C., Xuan, W., and Leung, M. K. H. 2010. A review on biodiesel production using catalyzed transesterification. Applied Energy 87:1083–1095. doi:10.1016/j.apenergy.2009.10.006.
  • Medeiros, M. F., Oliveira, H. N., Kurka, P., Meireles, A., and Sousa, E. B. D. 2006. Proposta de um reator para produção de biodiesel em fluídos supercríticos. Biodiesel O Novo Combustível Do Brasil 1:219–222.bk_AQCmts10b
  • Román-Figueroa, C., and Paneque, M. 2015. Ethics and Biofuel Production in Chile. Journal of Agricultural and Environmental Ethics 28:293–312. doi:10.1007/s10806-015-9535-1.
  • Smola, A., and Vapnik, V. 1997. Support vector regression machines. Advances in Neural Information Processing Systems 9:155–161.
  • Srivastava, A., and Prasad, R. 2000. Triglycerides-based diesel fuels. Renewable and Sustainable Energy Reviews 4:111–133. doi:10.1016/S1364-0321(99)00013-1.
  • Suykens, J. A. K., and Vandewalle, J. 1999. Least squares support vector machine classifiers. Neural Processing Letters 9:293–300. doi:10.1023/A:1018628609742.
  • Wang, L. 2005. Support vector machines: Theory and applications, Vol. 177. Berlin/Heidelberg, Germany: Springer Science & Business Media.
  • Warabi, Y., Kusdiana, D., and Saka, S. 2004. Reactivity of triglycerides and fatty acids of rapeseed oil in supercritical alcohols. Bioresource Technology 91:283–287. doi:10.1016/S0960-8524(03)00202-5.

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