温州市工商业用户用水行为预测分析数据

工商业用户用水量较大，通过采集其每日用水数据、用水设备数量和信息等，运用大数据构建其正常用水行为特征，确定正常用水时间范围和用水量范围等信息，从而对其用水行为进行预测。1、获取用户的历史数据，包括地区、户号、每日用水量（立方米）、设备编号等维度特征，运用大数据，对其进行历史行为分析，形成历史行为画像；2、通过用户的开户日期、安装日期、用水时间，结合GBDT算法进行建模，形成用户画像；3、通过DeepFM深度学习算法，结合历史行为画像和用户画像，并基于历史数据对用户进行用水行为预测，判断其是否存在用水行为异常。

Industrial and commercial (I&C) customers are typically characterized by high water consumption. To predict their water usage behavior, this dataset collects their daily water consumption data, quantity and detailed information of water-consuming equipment, etc., and applies big data technologies to construct the features of their normal water usage behavior, as well as determine the normal water use time window and water consumption range.
The specific workflow includes three steps:
1. Collect the user's historical data, including dimensional features such as region, household account number, daily water consumption (in cubic meters), equipment number, etc. Use big data technologies to conduct historical behavior analysis and establish a historical behavior profile;
2. Build a prediction model combined with the Gradient Boosting Decision Tree (GBDT) algorithm based on the user's account opening date, installation date and water usage time, to develop a targeted user profile;
3. Utilize the DeepFM deep learning algorithm, integrate the historical behavior profile and the user profile, and predict the user's water usage behavior based on historical data to identify whether there is abnormal water usage behavior.

搜集汇总

数据集介绍

特点

该数据集包含温州市工商业用户的用水数据，涵盖地区、户号、每日用水量等关键字段，共1003条记录，每日更新。通过历史行为分析和深度学习算法，预测用户用水行为异常，适用于工商业用水行为分析和异常检测。