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http://dx.doi.org/10.4491/KSEE.2012.34.5.312

Development and Validation of Multiple Regression Models for the Prediction of Effluent Concentration in a Sewage Treatment Process  

Min, Sang-Yun (Environmental Technology Institute, SEnbio)
Lee, Seung-Pil (Environmental Technology Institute, SEnbio)
Kim, Jin-Sik (Environmental Technology Institute, SEnbio)
Park, Jong-Un (Environmental Technology Institute, SEnbio)
Kim, Man-Soo (Environmental Technology Institute, SEnbio)
Publication Information
Journal of Korean Society of Environmental Engineers / v.34, no.5, 2012 , pp. 312-315 More about this Journal
Abstract
In this study, the model which can predict the quality of effluent has been implemented through multiple regression analysis to use operation data of a sewage treatment plant, to which a media process is applied. Multiple regression analysis were carried out by cases according to variable selection method, removal of outliers and log transformation of variables, with using data of one year of 2011. By reviewing the results of predictable models, the accuracy of prediction for $COD_{Mn}$ of treated water of secondary clarifiers was over 0.87 and for T-N was over 0.81. Using this model, it is expected to set the range of operating conditions that do not exceed the standards of effluent quality. In conclusion, the proper guidance on the effluent quality and energy costs within the operating range is expected to be provided to operators.
Keywords
Prediction; Control; Regression Analysis; Modeling; Regression Model;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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