Railway node data.

<div><p>Static models fail to track the fast-changing supply-demand balance in global logistics. For instance, the high-speed rail express corridor exhibits a transport capacity utilisation rate of less than 70% during peak periods, along with a node load imbalance of 0.57. Existing algo...

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Bibliographic Details
Main Author:	Dandan Wang (286632) (author)
Other Authors:	Ni Sun (11936027) (author)
Published:	2025
Subjects:	Ecology Science Policy Biological Sciences not elsewhere classified cost drops 28 convergence time overruns co &# 8322 capacity matching degree time optimization paradigm sudden demand changes second equilibrium convergence scale logistics networks reinforcement learning methods node load imbalance combines sparse gradient traditional methods objective optimization node network global logistics demand balance accelerated equilibrium tensor decomposition study proposes scalable real research innovates realizes sub prediction error peak periods framework achieves falls 27 existing algorithms driven framework disturbance recovery constrained multi changing supply benchmark performance 4 %,
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Railway node data.

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