解耦(概率)
功率消耗
计算机科学
功率(物理)
大数据
分离(统计)
消费(社会学)
功率优化
算法
数据挖掘
工程类
控制工程
机器学习
物理
社会学
量子力学
社会科学
作者
Yun Zhao,Junyi Chen,J. Fan
摘要
The multi-dimensional power consumption information decoupling and separation optimization algorithm based on power supply big data and user profile is a new algorithm applied in the power field. Through the analysis of big data in the power supply system, combined with user portraits, the power consumption habits and demand characteristics of users at different times and in different scenarios are obtained. Through the analysis and extraction of time-varying characteristics, the decoupling and separation of multi-dimensional power consumption information is realized, so as to better understand the impact of different factors on power consumption behavior. The advantage of this algorithm is that it can provide refined electricity consumption data and analysis results, thereby providing more intelligent and personalized services for power operators and users. By decoupling and separating multidimensional electricity consumption information, it is possible to gain a deeper understanding of users' electricity consumption behavior and needs, providing effective reference and support for the planning, operation, and management of power supply systems.
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