任刚红++杜坤++刘年东++周明++李诚

摘要：

混沌局域法预测模型适用于非线性、非平稳的城市日供水量预测，而邻近相点个数的选取对该模型预测精度有直接影响。传统方法通常以嵌入维m作为参考值，凭经验选取m+1个邻近相点，且仅使用欧式距离法计算当前相点距离，无法反映相点的运动趋势，易引入伪邻近相点，导致预测精度的降低。鉴于此，将演化追踪法引入城市日供水量预测，通过挖掘邻近相点的历史演化规律对参考样本进行优选，以提高预测精度。最后，采用实际日供水量数据验证所提出方法，结果表明，运用演化追踪法优选邻近相点能显著提高日供水量预测精度，预测平均绝对误差由2.501%降低到1.683%。

关键词：

混沌理论；局域法；邻近点；演化追踪法；供水量预测

Abstract：

The chaotic localregion forecasting model is suitable for nonlinear and nonstationary urban daily water supply forecast， and the neighbourhood selection has a direct impact on the model prediction accuracy. The traditional method usually takes the embedded dimension m as a reference， and selects m+1 nearest neighbours by experience. It usually introduces the pseudo nearest neighbours， which leads to the reduction of the prediction accuracy. Accordingly， the evolutionary tracing method is introduced into the prediction of urban daily water supply. By mining the historical evolution of nearest neighbours， the reference samples are optimized to improve the prediction accuracy. The proposed method is validated by the actual daily water supply data. The results show that the optimal approach is significantly improved by using evolutionary tracing method， and the average absolute error is reduced from 2.501% to 1.683%.

Keywords：

chaos；localregion method；neighbourhood selection；evolutionary tracing method； water supply forecast

现今水资源极度缺乏，城市供水优化调度显得尤为重要，而供水量预测又是供水优化调度的重要组成部分，其预测准确与否直接影响到给水系统调度决策能否是有效制定 [13]。供水系统是一个具有时变特性的复杂系统，其本身影响因子表现出非线性、非平稳的特性。供水量预测模型一般分为传统预测模型和基于新技术的方法模型，传统预测模型的参数筛选复杂，且多基于数学理论假设的基础上，预测效果难以保证。例如多元回归分析、统计预测法、专家意见法等[4]。混沌理论是一种新的预测技术，其通过历史观测数据， 找出蕴含其中的内在演化规律，对整个系统进行描述和解释，进而对系统做出预测。……