Prediction of Wastewater Treatment Plant Performance Using Multilinear Regression and Artificial Neural Networks
Küçük Resim Yok
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, modeling of Konya wastewater treatment plant was studied by using multilinear regression and artificial neural network with different architectures in SPSS and MATLAB software. All data were obtained from wastewater treatment plant of Konya during daily records over four month. Treatment efficiency of the plant was determined by taking into account the input values of pH, temperature, COD, TSS and BOD with output values of COD. To compare the performance of the model, coefficient of determination (R-2) and Mean Squared Error (MSE) were used. In Multilinear regression method, to understand the effects of the tested parameters, regression function was developed. The highest prediction efficiencies was obtained two hidden layers in Artificial Neural Network models. According to the modeling study, Artificial Neural Network models responded more satisfactory results than Multilinear Regression model.
Açıklama
International Symposium on Innovations in Intelligent SysTems and Applications (INISTA 2015) -- SEP 02-04, 2015 -- Madrid, SPAIN
Anahtar Kelimeler
modeling, multilinear regression, artificial neural network, performance
Kaynak
2015 INTERNATIONAL SYMPOSIUM ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA) PROCEEDINGS
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
