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• W2189027042 abstract "The water industry is striving hard to produce higher quality water at a lower cost due to increased regulatory standards. Municipal Water Treatment Plants can be considered as the industries producing potable water. They also produce huge amount of sludge after coagulation sedimentation in the clarri- flocculator unit which is a type of waste effluent containing large amount of aluminium and organic contaminants. Commonly it is discharged into surface water without proper treatment and hence causes water pollution. Aluminium salts extensively used for coagulation has been implicated in dialysis dementia, Parkinson and Alzheimer’s disease in Humans and also known to cause structural and functional problems in fishes, birds and animals. The present research work emphasizes to develop a green eco-friendly, clean and cost effective water treatment process to avoid the water pollution by non- judicious use of coagulant. Artificial Neural Network (ANN) technique is applied to the prediction of optimum coagulant dosing in Shyamala Water Treatment Plant, Bhopal. The alum sludge generated can be recycled and reused for waste water treatment." @default.
• W2189027042 created "2016-06-24" @default.
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• W2189027042 date "2013-01-01" @default.
• W2189027042 modified "2023-09-23" @default.
• W2189027042 title "Artificial Neural Network Modelling of Shyamala Water Works, Bhopal MP, India: A Green Approach towards the Optimization of Water Treatment Process" @default.
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