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According to the monitoring and analysis of chloroform in the water distribution network in a northern city of China, the variations of chloroform in the water distribution network and the major influence factors were studied. Using principle component analysis method, the prediction model which including 9 water quality indexes was established to predict the concentration of chloroform and the average prediction accuracy was more than 80%. Four prediction models, including neural network model and support vector machine model etc. were established using 4 conventional monitoring indexes such as temperature and residual chlorine. The average prediction accuracies of various models were in the range of 83.42% ~ 88.40%, which could absolutely fulfill practical requirements, namely, the adjustment measures could be taken in time basing on the prediction results to decrease the chloroform concentration in the water distribution network.
Date of Conference: 11-13 June 2009