Neural networks for long term prediction of fouling and backwash efficiency in ultrafiltration for drinking water production
The aim of this study was to develop a neural network model to predict the productivity of an ultrafiltration pilot plant, treating surface water to produce drinking water and operated with sequential backwashes. The model had to predict long-term performances of the pilot plant, it means to conside...
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| Veröffentlicht in: | Desalination 2000-12, Vol.131 (1), p.353-362 |
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| creator | Delgrange-Vincent, N. Cabassud, C. Cabassud, M. Durand-Bourlier, L. Laîné, J.M. |
| description | The aim of this study was to develop a neural network model to predict the productivity of an ultrafiltration pilot plant, treating surface water to produce drinking water and operated with sequential backwashes. The model had to predict long-term performances of the pilot plant, it means to consider both reversible and irreversible fouling. The model had also to take into account a minimum number of parameters. On site experiments were performed to constitute the learning and validation databases. The developed model consists in two interconnected recurrent neural networks. It allows predicting satisfactorily the filtration performances of the experimental pilot plant for different resource water quality and changing operating conditions. |
| doi_str_mv | 10.1016/S0011-9164(00)90034-1 |
| format | Article |
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Desalination</subject><subject>Drinking water production</subject><subject>Engineering Sciences</subject><subject>Environmental Engineering</subject><subject>Environmental Sciences</subject><subject>Exact sciences and technology</subject><subject>Fouling</subject><subject>Long-term modelling</subject><subject>Membrane separation (reverse osmosis, dialysis...)</subject><subject>Neural networks</subject><subject>Pollution</subject><subject>Ultrafiltration</subject><subject>Water treatment and pollution</subject><issn>0011-9164</issn><issn>1873-4464</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><recordid>eNqNkV1rFDEUhgdRcK3-BCEgiL0YPfmYZHIlpVQrLHqhXodMPmzc2aQmM10K_ngzs2Vv601CznnOe17yNs1rDO8xYP7hOwDGrcScvQM4lwCUtfhJs8G9oC1jnD1tNifkefOilN_1SSSlm-bvVzdnPaLopkPKu4J8ymhM8ReaXN6j2-xsMFNIESVfe_MYaktHiwZtdgddbpDzPpjgorlHIaJ5nLL2YTnXqUXO5hB3y9xBV9Gqmey8ar5snnk9Fvfq4T5rfn66-nF53W6_ff5yebFtDeNkajVhnWFEyJ7bYfC-64UDDxKooIZJIIPTXUdFJ7mBwQAXwHvMre6ttoIzetacH3Vv9Khuc9jrfK-SDur6YquWGhCKeyzIHa7s2yNbbf6ZXZnUPhTjxlFHl-aiiBQUY2D_ATLCZdc_CmLRY6C0q2B3BE1OpWTnT14xqCVptSatlhgVgFqTVovlNw8LdDF69FlHE8ppuCccS16pj0fK1Z--Cy6rssZWA87OTMqm8Mief_BXvS4</recordid><startdate>20001220</startdate><enddate>20001220</enddate><creator>Delgrange-Vincent, N.</creator><creator>Cabassud, C.</creator><creator>Cabassud, M.</creator><creator>Durand-Bourlier, L.</creator><creator>Laîné, J.M.</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>C1K</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0001-7554-8490</orcidid></search><sort><creationdate>20001220</creationdate><title>Neural networks for long term prediction of fouling and backwash efficiency in ultrafiltration for drinking water production</title><author>Delgrange-Vincent, N. ; Cabassud, C. ; Cabassud, M. ; Durand-Bourlier, L. ; Laîné, J.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c462t-a245c427986dbbff587e0f090373c4902bea5537596c0bc06706816da8dad7643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Applied sciences</topic><topic>Chemical and Process Engineering</topic><topic>Chemical engineering</topic><topic>Drinking water and swimming-pool water. Desalination</topic><topic>Drinking water production</topic><topic>Engineering Sciences</topic><topic>Environmental Engineering</topic><topic>Environmental Sciences</topic><topic>Exact sciences and technology</topic><topic>Fouling</topic><topic>Long-term modelling</topic><topic>Membrane separation (reverse osmosis, dialysis...)</topic><topic>Neural networks</topic><topic>Pollution</topic><topic>Ultrafiltration</topic><topic>Water treatment and pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Delgrange-Vincent, N.</creatorcontrib><creatorcontrib>Cabassud, C.</creatorcontrib><creatorcontrib>Cabassud, M.</creatorcontrib><creatorcontrib>Durand-Bourlier, L.</creatorcontrib><creatorcontrib>Laîné, J.M.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Desalination</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Delgrange-Vincent, N.</au><au>Cabassud, C.</au><au>Cabassud, M.</au><au>Durand-Bourlier, L.</au><au>Laîné, J.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neural networks for long term prediction of fouling and backwash efficiency in ultrafiltration for drinking water production</atitle><jtitle>Desalination</jtitle><date>2000-12-20</date><risdate>2000</risdate><volume>131</volume><issue>1</issue><spage>353</spage><epage>362</epage><pages>353-362</pages><issn>0011-9164</issn><eissn>1873-4464</eissn><coden>DSLNAH</coden><abstract>The aim of this study was to develop a neural network model to predict the productivity of an ultrafiltration pilot plant, treating surface water to produce drinking water and operated with sequential backwashes. 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| ispartof | Desalination, 2000-12, Vol.131 (1), p.353-362 |
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| source | Elsevier ScienceDirect Journals |
| subjects | Applied sciences Chemical and Process Engineering Chemical engineering Drinking water and swimming-pool water. Desalination Drinking water production Engineering Sciences Environmental Engineering Environmental Sciences Exact sciences and technology Fouling Long-term modelling Membrane separation (reverse osmosis, dialysis...) Neural networks Pollution Ultrafiltration Water treatment and pollution |
| title | Neural networks for long term prediction of fouling and backwash efficiency in ultrafiltration for drinking water production |
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