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Coagulationflocculation is well established waste water treatment process since many decades. In this present study, experimental investigations using jar tests were validated with response surface methodology (RSM) and Artificial Neural Network (ANN). RSM was applied to optimize the effects of processing parameters on the yield of BOD and COD removal and a computerstimulated artificial neural network (ANN) model was developed to get a good correlation between the input variables and the output parameter. This book, therefore, provides a novel approach for optimizing the process parameters during coagulationflocculation process using the statistical tools where dairy whey treatment has been achieved in a user friendly way. Moreover this particular approach can be implemented across the globe for all dairy industries (irrespective of their sizes) as that will definitely help the engineers/users in the dairy waste water treatment by optimizing the process variables of the experimental conditions while minimizing the number of required experiments.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer,
birth defects, or other reproductive harm.
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⚠️ California Proposition 65 Warning: Some products sold on this website may expose you to chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm. For more information, visit www.P65Warnings.ca.gov.
