Title :
The prediction of indices at infall of confluent flow network of wastewater with Multivariate Linear Regression
Author :
Gao Xiang ; Bai Lina
Author_Institution :
Autom. Sch., Yantai Nanshan Univ., Yantai, China
Abstract :
On the pre-estimation of indices of wastewater at the infall of Waste Water Treatment Plant (WWTP) in the confluent flow dynamic system,Multivariate Linear Regression (MLR) is presented and applied effectively in general case. However, the Partial Regression Coefficients (PRC) identified from the data model is not suitable for the continuous time varying process occasionally. Therefore, an improved Recursive Forgetting Factor Least Square (RFF-LS) algorithm for the regression of MLR is developed and implemented on an example of certain confluence flow system with a WWTP and relevant sources of wastewater to refresh the PRC adaptively now, which demonstrates better effect on predictive precision on indices of both Chemical Oxygen Demand (COD) concentration and water quantity.
Keywords :
continuous time systems; data models; least squares approximations; regression analysis; time-varying systems; wastewater treatment; chemical oxygen demand concentration; confluent flow dynamic system; continuous time varying process; data model; multivariate linear regression; partial regression coefficients; recursive forgetting factor least square algorithm; waste water treatment plant; water quantity; Estimation; Fitting; Heuristic algorithms; Indexes; Prediction algorithms; Wastewater; Wastewater treatment; COD; Confluent Flow; Multivariate Linear Regression; Partial Regression Coefficients; Recursive Forgetting Factor Least Square; Wastewater Treatment;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
