Partial least squares regression model to predict water quality in urban water distribution systems
Bijun Luo , Yuan Zhao , Kai Chen , Xinhua Zhao
Transactions of Tianjin University ›› 2009, Vol. 15 ›› Issue (2) : 140 -144.
Partial least squares regression model to predict water quality in urban water distribution systems
The water distribution system of one residential district in Tianjin is taken as an example to analyze the changes of water quality. Partial least squares (PLS) regression model, in which the turbidity and Fe are regarded as control objectives, is used to establish the statistical model. The experimental results indicate that the PLS regression model has good predicted results of water quality compared with the monitored data. The percentages of absolute relative error (below 15%, 20%, 30%) are 44.4%, 66.7%, 100% (turbidity) and 33.3%, 44.4%, 77.8% (Fe) on the 4th sampling point; 77.8%, 88.9%, 88.9% (turbidity) and 44.4%, 55.6%, 66.7% (Fe) on the 5th sampling point.
water distribution systems / water quality / turbidity / Fe / partial least squares regression
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