AI RESEARCH
Improving Spatial Allocation for Energy System Coupling with Graph Neural Networks
arXiv CS.LG
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ArXi:2602.22249v2 Announce Type: replace In energy system analysis, coupling models with mismatched spatial resolutions is a significant challenge. A common solution is assigning weights to high-resolution geographic units for aggregation, but traditional models are limited by using only a single geospatial attribute. This paper presents an innovative method employing a self-supervised Heterogeneous Graph Neural Network to address this issue.