NDLI: An intelligent modeling of coagulant dosing system for water treatment plants based on artificial neural network

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An intelligent modeling of coagulant dosing system for water treatment plants based on artificial neural network

Content Provider	Semantic Scholar
Author	Olanrewaju, Rashidah Funke Muyibi, Suleyman Aremu Salawudeen, Taofeeq Olalekan Aibinu, Abiodun Musa
Copyright Year	2012
Abstract	Coagulation –flocculation process remains a very essential part in the water treatment chain. It involves both physical and chemical phenomena and hence susceptible to high percentage of errors due to human factor. In order to reduce this percentage error and obtain optimal treatment efficiency, an intelligent coagulant dosing based on Artificial Neural Network (ANN) was proposed. Design of the Coagulant dosing using processed Moringa oleifera seed as coagulant was achieved through ANN that helps in water quality forecast and soft measure. Effort was made to suggest the optimization tips in the form of Artificial Intelligent tools that can be used for optimization of coagulation process. Such coagulant dosing based ANN will be a useful method to address most errors common in water treatment cause by human factors. Experimental results with simulated and real data show that the newly developed system is able to accurately predict coagulant dosage needed in water treatment for a small size rural community. The correlation between actual and ANN estimation of coagulant dosing model is 0.97 of 1.00. This high Correlation of coefficient indicates that the ANN model is a perfect match.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://ajbasweb.com/old/ajbas/2012/January/93-99.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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