是一个很好的短期水需求预测工具 运营商管理日常运营，节约能源使用。在本文中，作者 引入一种新策略，实时预测短期需水量。这 策略首先将当前的水需求与已知的需求模式或 动态需求模式，然后使用该模式作为指导，指导每小时的预测 接下来的24小时。作者证明，这种策略是两种策略的最佳混合 模式识别、时间序列分析和回归分析。它不仅继承了 从这三种方法中获得优势，但也获得了识别影响的能力 实时分析外部因素，并动态调整预测以提高准确性。 虽然通过需求分析预测需求的策略也有很大的潜力 如本文所示，在准备好进行测试之前，需要进行很多微调 工业应用。包括6个参考文献、表格、图表。

A reliable short-term water demand forecast would be a great tool to assist engineers and operators to manage daily operation and save energy usage. In this paper, the authors introduce a novel strategy to forecast short-term water demand in a real time base. This strategy first matches current water demands with either a known demand pattern or a dynamic demand pattern, then uses the pattern as a guide to direct the hourly predictions for next 24 hours. The authors demonstrate that this strategy is an optimal hybrid of pattern recognition, time series analysis and regression analysis. It not only inherits the advantages from these three approaches, but also gains the ability to recognize the impact of external factors in real time and dynamically adjusts the forecast for better accuracy. Although the strategy of forecasting demand with demand profiling has great potential as illustrated in this paper, there is much fine-tuning to be done before it is ready for industrial applications. Includes 6 references, tables, figures.