Beschreibung
Coagulation-flocculation 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 computer-stimulated 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 coagulation-flocculation 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.
Autorenporträt
Amitava Chakraborty is a final year M.Tech scholar at NIT,Durgapur,India in Biotech Department. He is also having the professional degree of Registered Indian Patent Agent with four years of consulting, litigation, and Intellectual Property research and project development experience.His research work was published in Indian Patent Office Journal.
