How-To Geek on MSN

Generate realistic test data in Python fast. No dataset required

Learn the NumPy trick for generating synthetic data that actually behaves like real data.
IEEE

Dynamic Graph Variational Sparse Coding for Power Distribution Network Fault Location and Classification

Abstract: Fault location and classification are crucial to the reliable and resilient operation of power distribution networks (PDNs). Current machine learning works cannot provide accurate and ...
IEEE

Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks

Abstract: Reactive power optimization of distribution networks is traditionally addressed by physical model based methods, which often lead to locally optimal solutions and require heavy online ...
Frontiers

Resilience optimization and dynamic stability defense in active distribution networks under extreme disasters: a graph learning and cooperative control approach

1 Guangdong Power Grid Corporation Foshan Power Supply Bureau, Foshan, China 2 Electric Power Research Institute of China Southern Power Grid, Guangzhou, Guangdong, China Introduction: The escalating ...