指出每种方法的优缺点，城市用水量预测应根据实际情况选取预测方法。以郑州市为例，选取不同的方法进行预测及分析，结果表明郑州市2020年之前的用水量呈现非线性递增的趋势。
Taking Zhengzhou as an example, choosing different methods to predict and analyze, the results indicate the increasing trend of the water consumption before 2020 in the city.
将偏最小二乘回归与神经网络耦合，建立了城市生活用水量预测模型。
The paper establishes the model for the urban life-water quantity prediction by means of combining neural network with the partial least squares method.
通过对城市用水量短期预测的实例研究，将改进算法与传统算法进行比较。
The improved method was compared with the traditional method in the case of short-term forecasting for urban water consumption.
城市生活用水量预测在城市水资源利用和节约用水规划管理中起着非常重要的作用。
The prediction of city municipal and domestic water consumption plays an important role in utilization of urban water resources.
通过分析验证的结果，证明了本文提出的城市日用水量预测模型可行，采用BP、R BF和SVM法求解方法均能得到满意的效果。
Analysis of the experimental results proved that the model of urban water consumption prediction is feasible, the BP network, the RBF network and SVM all can get the satisfied result.
分项预测了山西未来若干年的工农业及城市生活用水量，并分析了有关的计算误差。
A current computer programme will be used to predict the water consumption oF Shanxi Province on all water using issues such as agriculture, industry and daily living in the future years.
本文应用多元回归的方法，对城市用水量进行预测。
This article applies the multiplelinearregression to forecast city water consumption.
同时利用改进的季节性指数平滑法完成了对郑州市城市用水量的预测。
Using the improved seasonal exponential smoothing to finish the prediction of water consumption of Zhengzhou at the same time.
城市用水量需求预测常见的方法有经验预测法、统计分析法、规划估算法、灰色预测法。
Common methods of urban water needs prediction are experience prediction, statistic analysis, planning estimate, and grey prediction.
城市用水量需求预测常见的方法有经验预测法、统计分析法、规划估算法、灰色预测法。
Common methods of urban water needs prediction are experience prediction, statistic analysis, planning estimate, and grey prediction.
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