Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water
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oai:scholars.utp.edu.my:348042023-03-20T03:46:06Z http://scholars.utp.edu.my/id/eprint/34804/ Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water Boutra, B Sebti, A Trari, M Springer 2022 Article NonPeerReviewed Boutra, B and Sebti, A and Trari, M (2022) Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water. International Journal of Environmental Science and Technology, 19 (11). pp. 11263-11278. |
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Boutra, B Sebti, A Trari, M |
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Boutra, B Sebti, A Trari, M Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water |
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Boutra, B Sebti, A Trari, M |
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Boutra, B |
title |
Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water |
title_short |
Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water |
title_full |
Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water |
title_fullStr |
Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water |
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Response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water |
title_sort |
response surface methodology and artificial neural network for optimization and modeling the photodegradation of organic pollutants in water |
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Springer |
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2022 |
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http://scholars.utp.edu.my/id/eprint/34804/ |
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1761621144483397632 |
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