Research on a method for assessing the status of electric power metering assets based on neural network federated learning

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Authors

Publication Details

Journal
International Journal of Reasoning-based Intelligent Systems
Published
2025-01-01
DOI
https://doi.org/10.1504/ijris.2025.10074388
Primary Topic
Electricity Theft Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on a method for assessing the status of electric power metering assets based on neural network federated learning

Huinan Wang, Mingxin Jin, Guanna Lu, Shanshan Li et al.
International Journal of Reasoning-based Intelligent Systems
Electricity Theft Detection Techniques
article

Research on a method for assessing the status of electric power metering assets based on neural network federated learning

Huinan Wang, Mingxin Jin, Guanna Lu, Shanshan Li, Yang Lv
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Reasoning-based Intelligent SystemsVol. 1(1)
Openalex Percentile: Top 69%
Electricity Theft Detection Techniques
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Research on a method for assessing the status of electric power metering assets based on neural network federated learning — Huinan Wang, Mingxin Jin, et al. · International Journal of Reasoning-based Intelligent Systems (2025) | TGRS Research Map | TGRS