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Method of Predicting Residual Chlorine in Water Supply Systems

机译:供水系统中余氯的预测方法

摘要

A method of configuring an artificial neural network for predicting residual chlorine concentration in water contained in a storage tank of a water supply system, the storage tank having an inlet for admitting water into the tank and an outlet for discharging water from the tank. The method of the invention comprises the steps of (a) collecting historical data representative of selected operational and water quality parameters associated with chlorine demand in the tank; (b) scaling the data collected in step (a); (c) organizing the data scaled in step (b) in the form of a set of time-lagged data; and (d) processing the data organized in step (c) through an artificial neural network by scanning a window over the set of data, the window having a size corresponding to a sub-set of the data, to associate a predicted value with a respective one of the sub-sets scanned by the window, the predicted value being representative of the residual chlorine concentration at the tank outlet. The artificial neural network is thus configured to recognize a set of data processed therethrough as corresponding substantially to one of the sub-sets of data and to associate with the recognized set of data the optimized predicted value associated with the sub-set of data.
机译:一种构造人工神经网络的方法,该人工神经网络用于预测供水系统的储水箱中所含水中的残留氯浓度,该储水箱具有用于将水引入水箱的入口和用于从水箱中排出水的出口。本发明的方法包括以下步骤:(a)收集历史数据,该历史数据代表与罐中氯需求相关的所选操作和水质参数; (b)扩展在步骤(a)中收集的数据; (c)以一组时滞数据的形式组织在步骤(b)中缩放的数据; (d)通过人工神经网络处理步骤(c)中组织的数据,方法是扫描该组数据上的窗口,该窗口的大小与数据的子集相对应,以将预测值与窗口扫描的子集中的各个子集,预测值代表罐出口处的残余氯浓度。因此,人工神经网络被配置为将通过其处理的一组数据识别为基本上对应于数据子集之一,并且将与该数据子集相关联的优化的预测值与识别出的数据集相关联。

著录项

  • 公开/公告号CA2165400A1

    专利类型

  • 公开/公告日1997-06-16

    原文格式PDF

  • 申请/专利权人 UNIVERSITE LAVAL;

    申请/专利号CA19952165400

  • 发明设计人 RODRIGUEZ MANUEL;SERODES JEAN;

    申请日1995-12-15

  • 分类号G06F15/18;

  • 国家 CA

  • 入库时间 2022-08-22 03:23:43

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