Designing Channel Attention Fully Convolutional Networks with Neural Architecture Search for Customer Socio-Demographic Information Identification Using Smart Meter Data
<b>Background:</b> Accurately identifying the socio-demographic information of customers is crucial for utilities. It enables them to efficiently deliver personalized energy services and manage distribution networks. In recent years, machine learning-based data-driven methods have gained...
Saved in:
Main Authors: | Zhirui Luo, Qingqing Li, Ruobin Qi, Jun Zheng |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | AI |
Subjects: | |
Online Access: | https://www.mdpi.com/2673-2688/6/1/9 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Effects of Prepaid Metering Systems on Customer Satisfaction in Niger State, Nigeria
by: Ayooluwa Femi Aribisala, et al.
Published: (2021-12-01) -
Introduction of the novel and scarce meters in Simin Behbahani poetry
by: داود محمدی
Published: (2011-06-01) -
Searching heterogeneous collections on the Web: behaviour of Excite users
by: Amanda Spink, et al.
Published: (1998-01-01) -
Metering effects in population systems
by: Erika T. Camacho, et al.
Published: (2013-07-01) -
Evaluating the Performance of Smart Meters: Insights into Energy Management, Dynamic Pricing and Consumer Behavior
by: Konstantinos G. Koukouvinos, et al.
Published: (2025-01-01)