An artificial neural network combined with response surface methodology approach for modelling and optimization of the electro-coagulation for cationic dye.

Kothari, Manisha S; Vegad, Kinjal G; Shah, Kosha A; Aly Hassan, Ashraf

Kothari, Manisha S; Vegad, Kinjal G; Shah, Kosha A; Aly Hassan, Ashraf.

Afiliación

Kothari MS; Civil and Environmental Engineering Department, National Water and Energy Center, United Arab Emirates University, Al-Ain, Abu-Dhabi, United Arab Emirates.
Vegad KG; Civil Engineering Departments, Faculty of Technology and Engineering, The Maharaja Sayajirao University of Baroda, Vadodara, 390001, India.
Shah KA; Civil Engineering Departments, Faculty of Technology and Engineering, The Maharaja Sayajirao University of Baroda, Vadodara, 390001, India.
Aly Hassan A; Civil and Environmental Engineering Department, National Water and Energy Center, United Arab Emirates University, Al-Ain, Abu-Dhabi, United Arab Emirates.

Heliyon ; 8(1): e08749, 2022 Jan.

Article en En | MEDLINE | ID: mdl-35146148

Palabras clave

Artificial neural network; Colour removal efficiency; Electrical energy consumption; Electrocoagulation process; Response surface methodology

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2022 Tipo del documento: Article País de afiliación: Emiratos Árabes Unidos

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