Open Access
Issue
MATEC Web Conf.
Volume 379, 2023
18e Congrès de la Société Française de Génie des Procédés (SFGP2022)
Article Number 08004
Number of page(s) 9
Section Eau : un enjeu du futur / Water: A Challenge for the Future
DOI https://doi.org/10.1051/matecconf/202337908004
Published online 12 May 2023
  1. Asan, Umut, et Secil Ercan. 2012. « An Introduction to Self-Organizing Maps ». In Computational Intelligence Systems in Industrial Engineering: With Recent Theory and Applications, édité par Cengiz Kahraman, 295-315. Atlantis Computational Intelligence Systems. Paris: Atlantis Press. https://doi.org/10.2991/978-94-91216-77-0_14. [Google Scholar]
  2. Chang, Haiqing, Heng Liang, Fangshu Qu, Baicang Liu, Huarong Yu, Xing Du, Guibai Li, et Shane A. Snyder. 2017. « Hydraulic Backwashing for Low-Pressure Membranes in Drinking Water Treatment: A Review ». Journal of Membrane Science 540 (octobre): 362-80. https://doi.org/10.1016/j.memsci.2017.06.077. [CrossRef] [Google Scholar]
  3. Chen, Huaiqun, et Albert S. Kim. 2006. « Prediction of Permeate Flux Decline in Crossflow Membrane Filtration of Colloidal Suspension: A Radial Basis Function Neural Network Approach ». Desalination, International Congress on Membranes and Membrane Processes, 192 (1): 415-28. https://doi.org/10.1016/j.desal.2005.07.045. [Google Scholar]
  4. Commenge, Jean-Marc. s. d. « Big Data et Intelligence Artificielle pour le Génie des Procédés », 135. [Google Scholar]
  5. Hwang, Tae-Mun, Hyunje Oh, Yong-Jun Choi, Sook-Hyun Nam, Sangho Lee, et Youn-Kyoo Choung. 2009. « Development of a Statistical and Mathematical Hybrid Model to Predict Membrane Fouling and Performance ». Desalination 247 (1): 210-21. https://doi.org/10.1016/j.desal.2008.12.025. [CrossRef] [Google Scholar]
  6. Jacquet, Nolwenn. 2021. « Rétention des virus et nanoparticules par filtration membranaire : application à la production d’eau destinée à la consommation humaine ». These de doctorat, Aix-Marseille. https://www.theses.fr/2021AIXM0318. [Google Scholar]
  7. Kimura, Katsuki, et Keita Kume. 2020. « Irreversible Fouling in Hollow-Fiber PVDF MF/UF Membranes Filtering Surface Water: Effects of Precoagulation and Identification of the Foulant ». Journal of Membrane Science 602 (mai): 117975. https://doi.org/10.1016/j.memsci.2020.117975. [CrossRef] [Google Scholar]
  8. Niu, Chengxin, Xuesong Li, Ruobin Dai, et Zhiwei Wang. 2022. « Artificial Intelligence-Incorporated Membrane Fouling Prediction for Membrane-Based Processes in the Past 20 Years: A Critical Review ». Water Research 216 (juin): 118299. https://doi.org/10.1016/j.watres.2022.118299. [CrossRef] [Google Scholar]
  9. Peiris, Ramila H., Hector Budman, Christine Moresoli, et Raymond L. Legge. 2012. « FluorescenceBased Fouling Prediction and Optimization of a Membrane Filtration Process for Drinking Water Treatment ». AIChE Journal 58 (5): 1475-86. https://doi.org/10.1002/aic.12684. [CrossRef] [Google Scholar]
  10. Philippe, Nicolas, Anne-Emmanuelle Stricker, Yvan Racault, Alain Husson, Mathieu Sperandio, et Peter Vanrolleghem. 2013. « Modelling the Long-Term Evolution of Permeability in a FullScale MBR: Statistical Approaches ». Desalination 325 (septembre): 7-15. https://doi.org/10.1016/j.desal.2013.04.027. [CrossRef] [Google Scholar]
  11. Research and Markets. s. d. « Ultrafiltration Market by Type (Polymeric, and Ceramic), Module (Hollow Fiber), Application (Municipal, and Industrial (Food & Beverage Processing, Chemical & Petrochemical Processing, Pharma Processing)), and Region Global Forecast to 2023 ». Consulté le 28 juin 2022. https://www.researchandmarkets.com/reports/4602345/ultrafiltration-market-by-type-polymeric-and. [Google Scholar]
  12. Soleimani, Reza, Navid Alavi Shoushtari, Behrooz Mirza, et Abdolhamid Salahi. 2013. « Experimental Investigation, Modeling and Optimization of Membrane Separation Using Artificial Neural Network and Multi-Objective Optimization Using Genetic Algorithm ». Chemical Engineering Research and Design 91 (5): 883-903. https://doi.org/10.1016/j.cherd.2012.08.004. [CrossRef] [Google Scholar]
  13. Touffet, Arnaud. 2014. « Impact de la qualité de la ressource, des prétraitements et des lavages chimiques ». These de doctorat, Poitiers. https://www.theses.fr/2014POIT2340. [Google Scholar]
  14. Wehrens, Ron, et Johannes Kruisselbrink. 2018. « Flexible Self-Organizing Maps in Kohonen 3.0 ». Journal of Statistical Software 87 (novembre): 1-18. https://doi.org/10.18637/jss.v087.i07. [CrossRef] [Google Scholar]
  15. Yamamura, Hiroshi, Katsuki Kimura, Kumiko Higuchi, Yoshimasa Watanabe, Qing Ding, et Akira Hafuka. 2015. « Tracking Inorganic Foulants Irreversibly Accumulated on Low-Pressure Membranes for Treating Surface Water ». Water Research 87 (décembre): 218-24. https://doi.org/10.1016/j.watres.2015.09.018. [CrossRef] [Google Scholar]
  16. Yamamura, Hiroshi, Katsuki Kimura, et Yoshimasa Watanabe. 2014. « Seasonal Variation of Effective Chemical Solution for Cleaning of Ultrafiltration Membrane Treating a Surface Water ». Separation and Purification Technology 132 (août): 110-14. https://doi.org/10.1016/j.seppur.2014.04.043. [CrossRef] [Google Scholar]
  17. Yu, Haikuan, Haiqing Chang, Xing Li, Zhiwei Zhou, Wuchang Song, Hongjie Ji, et Heng Liang. 2021. « Long-Term Fouling Evolution of Polyvinyl Chloride Ultrafiltration Membranes in a Hybrid Short-Length Sedimentation/ Ultrafiltration Process for Drinking Water Production ». Journal of Membrane Science 630 (juillet): 119320. https://doi.org/10.1016/j.memsci.2021.119320. [CrossRef] [Google Scholar]
  18. Zhang, Bopeng, Georgios Kotsalis, Jahanzeb Khan, Zhaoyang Xiong, Thomas Igou, Guanghui Lan, et Yongsheng Chen. 2020. « Backwash Sequence Optimization of a Pilot-Scale Ultrafiltration Membrane System Using Data-Driven Modeling for Parameter Forecasting ». Journal of Membrane Science 612 (octobre): 118464. https://doi.org/10.1016/j.memsci.2020.118464. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.