References
- Abu Al-Rub, F. A., and R. Datta. 1999. Separation of 2-propanol–water mixture with capillary porous plates. Separation Science and Technology 34 (5):725–42. doi:10.1080/01496399908951141.
- Acevedo, L., J. Uche, and D. A. Del-Amo. 2018. Improving the distillate prediction of a membrane distillation unit in a trigeneration scheme by using artificial neural networks. Water 10 (3):310. doi:10.3390/w10030310.
- Al-Rub, F. A. A. 2002. Prediction of vapor-liquid equilibrium inside capillary porous plates. Chemical Engineering & Technology 25 (12):1171–75.
- Al-Rub, F. A. A., J. Akili, and R. Datta. 1998. Distillation of binary mixtures with capillary porous plates. Separation Science and Technology 33 (10):1529–50. doi:10.1080/01496399808545064.
- Chen, J. X., Q. Ye, T. Liu, H. Xia, and S. Y. Feng. 2019. Improving the performance of heterogeneous azeotropic distillation via self-heat recuperation technology. Chemical Engineering Research & Design 141:516–28. doi:10.1016/j.cherd.2018.11.022.
- Dantas, T., T. Cabral, A. Neto, and M. C. P. A. Moura. 2020. Enrichmnent of patchoulol extracted from patchouli (Pogostemon cablin) oil by molecular distillation using response surface and artificial neural network models. Journal of Industrial & Engineering Chemistry 81:219–27. doi:10.1016/j.jiec.2019.09.011.
- Gao, J., H. Tembine, Distributed mean-field-type filters for big data assimilation, in the second IEEE International Conference on Data Science and Systems (HPCC-SmartCity-DSS), Sydney, Australia, Dec, 2016; pp. 1446–53.
- Gao, J., and H. Tembine. 2019. Distributed mean-field-type filters for traffic networks. IEEE Transactions on Intelligent Transportation Systems 20 (2):507–21. doi:10.1109/TITS.2018.2816811.
- Jiang, H., Z. L. Xi, A. A. Rahman, and X. Zhang. 2020. Prediction of output power with artificial neural network using extended datasets for Stirling engines. Applied Energy 271 (1):115123. doi:10.1016/j.apenergy.2020.115123.
- Jiang, Z., and R. Agrawal. 2019. Process intensification in multicomponent distillation: A review of recent advancements. Chemical Engineering Research & Design 147:122–45. doi:10.1016/j.cherd.2019.04.023.
- Jiao, Y. Y., M. Yan, X. L. Wang, J. H. Zhong, Y. S. Chen, W. G. Zhu, X. Li, Z. Y. Zhu, P. Z. Cui, Y. Y. Lu, et al. 2023. Economic, environmental, energy and exergy analysis and multi-objective optimization for efficient purification of a friendly gasoline additive by extractive distillation coupled with pervaporation. Fuel 335:127069. doi:10.1016/j.fuel.2022.127069.
- Kim, B., Y. Choi, J. Choi, Y. Shin, and S. Lee. 2020. Effect of surfactant on wetting due to fouling in membrane distillation membrane: Application of response surface methodology (RSM) and artificial neural networks (ANN). The Korean Journal of Chemical Engineering 37 (1):1–10. doi:10.1007/s11814-019-0420-x.
- Li, B. F., B. Qi, Z. Y. Guo, D. X. Wang, and T. F. Jiao. 2023. Recent developments in the application of membrane separation technology and its challenges in oil-water separation: A review. Chemosphere 327:138528. doi:10.1016/j.chemosphere.2023.138528.
- Li, X. H., Q. Ye, J. L. Li, Y. J. Liu, L. Q. Yan, X. Jian, and J. Y. Zhang. 2023. Investigation on energy-efficient heterogeneous pressure-swing azeotropic distillation for recovery of cyclohexane and tert-butanol from industrial effluent. Separation and Purification Technology 306:122705. doi:10.1016/j.seppur.2022.122705.
- Liu, X. Y., J. H. Wu, Y. Lei, X. Q. Wu, Y. Man, H. Luo, and Q. G. Xiong. 2023. Data-driven surrogate optimized and intensified extractive distillation process for clean separation of isopropanol from water: A sustainable alternative. Journal of Cleaner Production 383:135475. doi:10.1016/j.jclepro.2022.135475.
- Mittal, S., A. Gupta, S. Srivastava, and M. Jain. 2021. Artificial neural network based modeling of the vacuum membrane distillation process: Effects of operating parameters on membrane fouling. Chemical Engineering & Processing - Process Intensification 164:108403. doi:10.1016/j.cep.2021.108403.
- Wong, N. S. J. 1997. The effects of capillary plates on vapor-liquid equilibrium in aqueous alcohol systems. Montreals: McGill University.
- Xu, J. L. 2020. Application and research progress of artificial neural network in simulation of wastewater treatment process. Modern Business Trade Industry 41 (08):202–04.
- Yeh, G. C. 1978. Separation of liquid lixtures: US4118285[P].
- Zhai, J., X. Chen, X. Q. Sun, and H. F. Xie. 2023. Economically and thermodynamically efficient pressure-swing distillation with heat integration and heat pump techniques. Applied Thermal Engineering 218:119389. doi:10.1016/j.applthermaleng.2022.119389.