Prediction of the optimal dosage of coagulants in water treatment plants through developing models based on artificial neural network fuzzy inference system (ANFIS) | Zendy

Shakeri Narges | Zendy; Ghorban Asgari | Zendy; Hassan Khotanlou | Zendy; Mohammad Khazaei | Zendy

Open Access

Prediction of the optimal dosage of coagulants in water treatment plants through developing models based on artificial neural network fuzzy inference system (ANFIS)

Author(s) -

Shakeri Narges,

Ghorban Asgari,

Hassan Khotanlou,

Mohammad Khazaei

Publication year - 2021

Publication title -

journal of environmental health science and engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.447

H-Index - 45

ISSN - 2052-336X

DOI - 10.1007/s40201-021-00710-0

Subject(s) - adaptive neuro fuzzy inference system , raw water , coagulation , turbidity , water treatment , artificial neural network , alum , alkalinity , inference system , neuro fuzzy , flocculation , water quality , mean squared error , mathematics , pulp and paper industry , biological system , artificial intelligence , chemistry , environmental engineering , environmental science , computer science , fuzzy logic , fuzzy control system , engineering , statistics , biology , ecology , psychology , organic chemistry , psychiatry

Coagulation and flocculation are the prominent processes and unit-operations in water treatment plants. One of the most challenging operations in water treatment process is determining of the coagulant dose.

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