邢台市大用户异常用水评分数据
收藏资源简介:
通过整合大用户远传及营收抄表数据,从设备离线、水量异常、超期服役、精度偏差、营业对比、违章稽查六个维度进行评分分析,筛选低分用户,供水务公司管理决策。1、数据获取 获取用户号、水表编号、用户名称、日用水量(m³)。 2、规则设定 选定6个判断大用户存在异常的分析维度,根据综合评分法,每日执行分值计算。 从设备离线(分)、水量异常(分)、超期服役(分)、精度偏差(分)、营业对比(分)、违章稽查(分)六个维度进行评分计算,每个维度设定不同的扣分标准及处置建议,单个维度最高5分,满分30分。 3、结果输出 输出评分日期及综合得分(分),筛选出特定日期的低分大用户,并可查看具体的扣分模块及扣分原因。
This dataset integrates remote transmission and revenue meter reading data of large-scale water consumers, conducts scoring analysis across six dimensions including equipment offline status, abnormal water consumption, overdue service, accuracy deviation, business comparison, and violation inspection, screens out low-scoring users, and provides support for management decision-making of water supply companies. 1. Data Acquisition Acquire user ID, water meter number, user name, and daily water consumption (m³). 2. Rule Setting Six analysis dimensions for detecting abnormalities in large-scale water consumers are selected, and daily score calculation is implemented via the comprehensive scoring method. Scoring is carried out across the six dimensions: equipment offline status (points), abnormal water consumption (points), overdue service (points), accuracy deviation (points), business comparison (points), and violation inspection (points). Each dimension has distinct deduction standards and corresponding disposal suggestions, with the maximum score for a single dimension being 5 points and the total full score reaching 30 points. 3. Result Output Output the scoring date and comprehensive score (points), screen out low-scoring large-scale water consumers on specific dates, and enable users to view specific deduction modules and their corresponding deduction reasons.




