苍南市大用户异常用水分析数据

通过大用户水表营收抄表数据集，分析用水变化规律，并根据不同水量区间，设定异常判断标准，筛选水量异常下降的大用户，判断水量下降原因，供水务公司管理决策.1、数据获取
获取用户号、用户名称、水表口径（mm）、上次换表时间、下次换表时间、日期
2、规则设定
①根据水表口径（mm），设定不同口径水表的理论换表年限（年）。
②设定结论判断条件，根据超期服役，月均用水变化（m³/月）及历年水量变化（m³/年）设置判断条件。
3、结果输出
使用ARIMA模型，每月执行计算，用当月数据对比设定的判断条件，生成分析结论。

This dataset leverages the revenue meter reading data of large water users to analyze water consumption variation patterns, set anomaly detection criteria based on different water volume ranges, screen out large users with abnormal water volume declines, identify the causes of such declines, and support management decision-making for water supply companies.
1. Data Acquisition
Obtain user ID, user name, water meter caliber (mm), last meter replacement time, next scheduled meter replacement time, and collection date.
2. Rule Setting
① Set the theoretical service life (in years) for water meters of different calibers based on their water meter caliber (mm).
② Define conclusion judgment conditions, which are formulated based on overdue service status, monthly average water consumption variation (m³/month) and annual historical water consumption variation (m³/year).
3. Result Output
Execute monthly calculations using the ARIMA model, compare the current month's data against the pre-set judgment conditions, and generate corresponding analysis conclusions.

搜集汇总

数据集介绍

特点

该数据集包含601条苍南市大用户的异常用水分析数据，每月更新，用于通过分析用水变化规律和设定异常判断标准，帮助水务公司管理决策。数据包括用户号、用户名称、水表口径、上次换表时间等关键字段，并通过ARIMA模型生成分析结论。