Abstract: The state data of system operation is the product of the interaction of complex factors,and the change of water demand is affected by many factors.The traditional time series prediction method has a single predictor variable,ignoring the causal relationship of various factors of the system.Therefore,this paper proposed a new prediction method,namely Fuzzy Cognitive Map (FCM),which exactly has this kind of feature.It is a fuzzy feedback reasoning mechanism with weight value,which quantifies the causal relationship between concepts and simulates the entire system is running.This paper combined the fuzzy cognitive map and the genetic algorithm to construct the urban water demand model,collected and organized the data at 2001~2010,and finally used the data at 2011~2015 for verification and test.The results show that in terms of the five-year average relative error,the nonlinear trend model is 5.91%,the BP neural network is 1.83%,and the method of this paper is 1.34%.Therefore,the prediction accuracy of this method is higher and the generalization performance is good.According to the analysis of experimental data,in the future,the management of water resources in Jinan City should properly control the water consumption of GDP and the water consumption of industrial added value,and increase the urban industrial water reuse rate and the domestic water recovery rate.This model provides a more efficient method for urban water demand forecasting and analysis.

Key words: Fuzzy cognitive map, Genetic algorithm, Urban water demand forecast