第39泰第4期 2017年8月
土水建筑与环境工程
Journal of Civil,Architectural &. Environmental Engineering
doi:10.11835/j.issn.1674-4764.2017.04.016
局域法邻近点选取对供水量预测精度
的影响
任刚红，杜坤，刘年东，周明，李诚（昆明理工大学建筑工程学院，昆明650500）
Vol. 39 No. 4 Aug. 2017
摘要：混沌局域法预测模型适用于非线性、非平稳的市日供水量预测，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十1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
中图分类号：TP183
文献标志码：A文章编号：1674-4764(2017)04-0102-05
Influenceof select thelocal-regionmethodnearestneighbours
onwatersupplyforecastingaccuracy
Ren Ganghong,Du Kun,Liu Niandong,Zhou Ming,Li Cheng
(Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology , Kunming, 650500, P. R. China) Abstract : The chaotic local-region forecasting model is suitable for nonlinear and non-stationary 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+] 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
收稿日期：2016-12-03
基金项目：国家自然科学基金（51608242)；昆明理工大学2016年学生课外学术科技创新基金（2015YB025）；云南省人才
培养计划（14118943）
作者简介：任刚红（1992-），女，主要从事市政工程研究，（E-mail)554769994@qq.com
杜坤（通信作者），男，博士，（E-mail）250977426@qq.com
Received:2016-12-03
Foundation item: National Natural Science Foundation of China (No. 51608242); Kunming University of Science and
Technology, 2016 Students Extracurricular Academic Science and Technology Innovation Fund (No. 2015YBo25); Personnel Training Program of Yunnan Province (No.14118943)
Author brief: Ren Ganghong(1992) , main research interest : municipal engineering , (E-mail)554769994@qq. com.
Du Kun(corresponding author), PhD,(E-mail) 250977426@qq. com
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