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An intercorrelated multi-node skin temperature model using MODWT-GAT and a case study in plateau tunnels
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DOI：10.1016/j.xcrp.2026.103105.png)
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Abstract
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• MODWT-GAT enables intercorrelation analysis of multi-node skin temperature • The average classification accuracy across six extreme conditions is 93.18% • Dominant graph features differ between normobaric and hypobaric conditions
Keywords:
skin temperature
thermal response
intercorrelation
wavelet transform
graph neural network
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