Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater

Raheleh Jafari, Sina Razvarz, Wen Yu, Alexander Gegov, Morten Goodwin, Mo Adda

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferencia

Resumen

The existence of C.I. Acid Yellow 23 (AY23) in water causes a great danger to people and society. Here, we suggest an advanced technique which predicts the photochemical deletion of AY23. The genetic algorithm (GA) technique is suggested in order to predict the photocatalytic removal of AY23 by implementing the Ag-TiO2 nanoparticles provided under appropriate conditions. In order to evaluate the proposed method, a total of 100 data are utilized which are arbitrarily divided into two: 80 samples in order to train the model as well as 20 samples in order to test the model. Experimental outcomes reveals that the suggested technique is efficient for photocatalytic elimination of impurity in wastewater.

Idioma originalInglés
Título de la publicación alojadaIntelligent Systems and Applications - Proceedings of the 2019 Intelligent Systems Conference IntelliSys Volume 1
EditoresYaxin Bi, Rahul Bhatia, Supriya Kapoor
EditorialSpringer Verlag
Páginas228-236
Número de páginas9
ISBN (versión impresa)9783030295158
DOI
EstadoPublicada - 1 ene 2020
EventoIntelligent Systems Conference, IntelliSys 2019 - London, Reino Unido
Duración: 5 sep 20196 sep 2019

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1037
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

ConferenciaIntelligent Systems Conference, IntelliSys 2019
PaísReino Unido
CiudadLondon
Período5/09/196/09/19

Huella dactilar

Wastewater
Genetic algorithms
Impurities
Acids
Nanoparticles
Water

Citar esto

Jafari, R., Razvarz, S., Yu, W., Gegov, A., Goodwin, M., & Adda, M. (2020). Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater. En Y. Bi, R. Bhatia, & S. Kapoor (Eds.), Intelligent Systems and Applications - Proceedings of the 2019 Intelligent Systems Conference IntelliSys Volume 1 (pp. 228-236). (Advances in Intelligent Systems and Computing; Vol. 1037). Springer Verlag. https://doi.org/10.1007/978-3-030-29516-5_17
Jafari, Raheleh ; Razvarz, Sina ; Yu, Wen ; Gegov, Alexander ; Goodwin, Morten ; Adda, Mo. / Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater. Intelligent Systems and Applications - Proceedings of the 2019 Intelligent Systems Conference IntelliSys Volume 1. editor / Yaxin Bi ; Rahul Bhatia ; Supriya Kapoor. Springer Verlag, 2020. pp. 228-236 (Advances in Intelligent Systems and Computing).
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title = "Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater",
abstract = "The existence of C.I. Acid Yellow 23 (AY23) in water causes a great danger to people and society. Here, we suggest an advanced technique which predicts the photochemical deletion of AY23. The genetic algorithm (GA) technique is suggested in order to predict the photocatalytic removal of AY23 by implementing the Ag-TiO2 nanoparticles provided under appropriate conditions. In order to evaluate the proposed method, a total of 100 data are utilized which are arbitrarily divided into two: 80 samples in order to train the model as well as 20 samples in order to test the model. Experimental outcomes reveals that the suggested technique is efficient for photocatalytic elimination of impurity in wastewater.",
keywords = "Ag-TiO, C.I. Acid Yellow 23, Genetic algorithm, Wastewater",
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Jafari, R, Razvarz, S, Yu, W, Gegov, A, Goodwin, M & Adda, M 2020, Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater. En Y Bi, R Bhatia & S Kapoor (eds.), Intelligent Systems and Applications - Proceedings of the 2019 Intelligent Systems Conference IntelliSys Volume 1. Advances in Intelligent Systems and Computing, vol. 1037, Springer Verlag, pp. 228-236, London, Reino Unido, 5/09/19. https://doi.org/10.1007/978-3-030-29516-5_17

Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater. / Jafari, Raheleh; Razvarz, Sina; Yu, Wen; Gegov, Alexander; Goodwin, Morten; Adda, Mo.

Intelligent Systems and Applications - Proceedings of the 2019 Intelligent Systems Conference IntelliSys Volume 1. ed. / Yaxin Bi; Rahul Bhatia; Supriya Kapoor. Springer Verlag, 2020. p. 228-236 (Advances in Intelligent Systems and Computing; Vol. 1037).

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferencia

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T1 - Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater

AU - Jafari, Raheleh

AU - Razvarz, Sina

AU - Yu, Wen

AU - Gegov, Alexander

AU - Goodwin, Morten

AU - Adda, Mo

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N2 - The existence of C.I. Acid Yellow 23 (AY23) in water causes a great danger to people and society. Here, we suggest an advanced technique which predicts the photochemical deletion of AY23. The genetic algorithm (GA) technique is suggested in order to predict the photocatalytic removal of AY23 by implementing the Ag-TiO2 nanoparticles provided under appropriate conditions. In order to evaluate the proposed method, a total of 100 data are utilized which are arbitrarily divided into two: 80 samples in order to train the model as well as 20 samples in order to test the model. Experimental outcomes reveals that the suggested technique is efficient for photocatalytic elimination of impurity in wastewater.

AB - The existence of C.I. Acid Yellow 23 (AY23) in water causes a great danger to people and society. Here, we suggest an advanced technique which predicts the photochemical deletion of AY23. The genetic algorithm (GA) technique is suggested in order to predict the photocatalytic removal of AY23 by implementing the Ag-TiO2 nanoparticles provided under appropriate conditions. In order to evaluate the proposed method, a total of 100 data are utilized which are arbitrarily divided into two: 80 samples in order to train the model as well as 20 samples in order to test the model. Experimental outcomes reveals that the suggested technique is efficient for photocatalytic elimination of impurity in wastewater.

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Jafari R, Razvarz S, Yu W, Gegov A, Goodwin M, Adda M. Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater. En Bi Y, Bhatia R, Kapoor S, editores, Intelligent Systems and Applications - Proceedings of the 2019 Intelligent Systems Conference IntelliSys Volume 1. Springer Verlag. 2020. p. 228-236. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-29516-5_17