Research on model of gray prediction of urban water demand based on genetic algorithm：taking project of water diversion from Qinglong River to Qinhuangdao for example
Through data analysis and combined with the characteristics of traditional gray GM(1,1) model, the paper presented improved GM(1,1,λ) model based on genetic algorithm and metabolism. The results indicated that prediction accuracy of GM(1,1) model is lower for scattered data, its accuracy level is under the forth and the maximum relative error is 45%. The predictive value is increased year by year,which is inconsistent with the actual situation. The prediction accuracy level of improved GM(1,1,λ) model is the third and the maximum relative error is 18.716%,which better reflects the change trend of urban water demand and is most close to the observation data,and the prediction accuracy is higher.