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Logistic regression for prediction and diagnosis of bacterial regrowth in water distribution system

Logistic regression for prediction and diagnosis of bacterial regrowth in water distribution system,10.1007/s12209-009-0065-7,Transactions of Tianjin

Logistic regression for prediction and diagnosis of bacterial regrowth in water distribution system  
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This paper focuses on the quantitative expression of bacterial regrowth in water distribution system. Considering public health risks of bacterial regrowth, the experiment was performed on a distribution system of selected area. Physical, chemical, and microbiological parameters such as turbidity, temperature, residual chlorine and pH were measured over a three-month period and correlation analysis was carried out. Combined with principal components analysis (PCA), a logistic regression model is developed to predict and diagnose bacterial regrowth and locate the zones with high risks of microbiology in the distribution system. The model gives the probability of bacterial regrowth with the number of heterotrophic plate counts as the binary response variable and three new principal components variables as the explanatory variables. The veracity of the logistic regression model was 90%, which meets the precision requirement of the model.
Journal: Transactions of Tianjin University , vol. 15, no. 5, pp. 371-374, 2009
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