An early fouling alarm method for a ceramic microfiltration pilot plant using machine learning

Author:

Tak Dohyun,Kim Dongkeon,Jeon Jongmin,Kim Suhan

Publisher

The Korean Society of Water and Wastewater

Subject

General Medicine

Reference20 articles.

1. Blum, A.L. , and Langley, P. (1997). Selection of relevant features and examples in machine learning, Artif. Intell., 97, 245– 271.

2. Choi, B. (2007). Influence of conditions for pre-treatment, aeration intensity and methods of backwash on micro-filter fouling in water treatment, Master’s Thesis, Yonsei University.

3. Dalmau, M. , Rodriguez-Roda, I. , Ayesa, E. , Odriozola, J. , Sancho, L. , and Comas, J. (2013). Development of a decision tree for the integrated operation of nutrient removal MBRs based on simulation studies and expert knowledge, J. Chem. Eng., 217, 174-184.

4. Dong-Ah Geological Engineering (2012). Assessment of applicability by ceramic membrane filtration process at Beomeosa water treatment plant, Research report.

5. Hall, M.A. , and Smith, L.A. (1998). Practical feature subset selection for machine learning, Comput. Sci., 98, 181–191.

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