| 基于最小二乘支持向量机的城市供水短期水量预测研究 |
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| 引用本文： | 朱慧峰.基于最小二乘支持向量机的城市供水短期水量预测研究[J].电气自动化,2018(1):105-107. |
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| 作者姓名： | 朱慧峰 |
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| 作者单位： | 上海市供水调度监测中心,上海,200085 |
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| 基金项目： | 此项工作得到国家科技重大专项项目(2017ZX07207003)，国家自然基金科学基金重点项目(61233004)，上海市科学技术委员会科研计划项目(16DZ1201202) |
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| 摘 要： | 以上海市供水调度中心智能调度运行管理系统为背景,研究智能调度子系统——水量预测系统的建立及运行,建立基于改进型引力搜索算法-最小二乘支持向量机的城市小时级和天级供水量预测模型,并应用于上海市中心城区和郊县各水厂的供水水量预测研究,实现了城市小时级和天级供水水量预测。
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| 关 键 词： | 城市供水 水量预测 支持向量机 预测模型 搜索算法 city water supply water volume prediction support vector machine prediction model searching algorithm |
Predictive Study on Short-term Urban Water Supply Based on Least Squares Support Vector Machines |
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| Zhu Huifeng.Predictive Study on Short-term Urban Water Supply Based on Least Squares Support Vector Machines[J].Electrical Automation,2018(1):105-107. |
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| Authors: | Zhu Huifeng |
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| Abstract: | Based on the intelligent management system for scheduling and operation of Shanghai Water Supply & Control Center,the establishment and operation of intelligent scheduler subsystem-water volume prediction system was studied.The prediction model of water supply volume per urban hour and per day based on the improved gravity search algorithm-least square support vector machines was established and applied to the predictive study of water supply volume in the waterworks of downtown and suburban counties in Shanghai.So that it is possible to realize prediction of water supply volume per city hour and per day. |
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