کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
567595 876111 2012 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
New data mining and calibration approaches to the assessment of water treatment efficiency
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
پیش نمایش صفحه اول مقاله
New data mining and calibration approaches to the assessment of water treatment efficiency
چکیده انگلیسی

For the first time, the application of different robust data mining techniques to the assessment of water treatment performance is considered. Principal components analysis (PCA), parallel factor analysis (PARAFAC), and a self-organizing map (SOM) were used in the analysis of multivariate data characterising organic matter (OM) removal at 16 water treatment works. Decomposed fluorescence data from PCA, PARAFAC and SOM were used as input to calibrate fluorescence data with OM concentrations using stepwise regression (SR), partial least squares (PLS), multiple linear regression (MLR), and neural network with back-propagation algorithm (BPNN). The best results were obtained with combined PARAFAC/PLS and SOM/BPNN. Both the numerical accuracy and feasibility of the adopted solutions were compared and recommendations on the use of the above techniques for fluorescence data analysis are presented.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 44, Issue 1, February 2012, Pages 126–135
نویسندگان
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