嘉兴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 users have relatively high water consumption. By collecting their daily water consumption data, quantity and relevant information of water-using equipment, big data techniques are adopted to construct the characteristics of their normal water usage behaviors, define the normal time range and water consumption range, thereby facilitating water use behavior prediction.
1. Collect historical user data covering dimensional features such as region, household number, daily water consumption (in cubic meters), equipment number, etc., perform historical behavior analysis via big data to establish a historical behavior profile;
2. Develop models using the GBDT algorithm in combination with the user's account opening date, installation date and water use time to generate a user profile;
3. Apply the DeepFM deep learning algorithm, integrate the historical behavior profile and user profile, and predict the user's water use behavior based on historical data to detect abnormal water use behaviors.

搜集汇总

数据集介绍

特点

该数据集包含嘉兴市工商业用户的用水数据，如每日用水量、用水时间等，共1092条记录，每日更新。通过GBDT和DeepFM算法分析用户用水行为，预测异常情况，适用于工商业用水行为预测和管理。