基于LightGBM的水厂供水压力预测
FORECASTING OF WATER SUPPLY PRESSURE BASED ON LIGHTGBM
耿为民 1颜军 2张典 3马平川 4阳国华5
作者信息
- 1. 上海城建职业学院市政与生态工程学院 上海 200438
- 2. 山东沃特兰德环境科技有限公司 山东枣庄 277101
- 3. 上海柯林布瑞信息技术有限公司 上海 200233
- 4. 上海出版印刷高等专科学校信息与智能工程系 上海 200093
- 5. 上海市计算技术研究所有限公司 上海 200040
- 折叠
摘要
针对城市供水管网调度问题,提出一种基于LightGBM(Light Gradient Boosting Machine)的水厂供水压力预测模型.对压力监测点历史数据提取时间特征,并根据特征重要性对测压点排序,以特征权重筛选、特征权重与经验相结合两种方式选取控制点.以南方某城市供水系统为算例,结果表明采用特征权重分析、人工经验相结合选用控制点来预测,具有较高和稳定的预测精度.
Abstract
Aimed at the scheduling problem of urban water distribution system,a water supply pressure prediction model based on LightGBM(Light Gradient Boosting Machine)is proposed.The time characteristics of the historical data on pressure monitoring points were extracted.The monitoring points were sorted according to the feature importance.The control points were selected in two ways:one was according to feature weight,and the other one was combined feature weight and experience.Taking a water supply system in southern China as a research case,the results show it has high and stable prediction accuracy that the control points are selected by combining feature weight analysis and scheduling experience.
关键词
供水系统/压力预测/特征权重/LightGBMKey words
Water distribution system/Pressure forecast/Feature weight/LightGBM引用本文复制引用
基金项目
上海市住房和城乡建设管理委员会科研项目(沪建科2021002056)
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据