To address the trade-off between accuracy and cross-city generalization in traffic flow estimation, a research team from The ...
Abstract: Traditional optimization-based techniques for time-synchronized state estimation (SE) often suffer from high online computational burden, limited phasor measurement unit (PMU) coverage, and ...
Network-wide traffic flow, which represents the dynamic traffic volumes on each link of a road network, is fundamental to smart cities. However, the ...
Abstract: Multi-task learning (MTL) is a standard learning paradigm in machine learning. The central idea of MTL is to capture the shared knowledge among multiple tasks for mitigating the problem of ...
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