H
Hai Yang
Researcher at Hong Kong University of Science and Technology
Publications - 431
Citations - 23953
Hai Yang is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Traffic congestion & Flow network. The author has an hindex of 73, co-authored 426 publications receiving 19789 citations. Previous affiliations of Hai Yang include University of California, Davis & Beihang University.
Papers
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Urban Computing: Concepts, Methodologies, and Applications
TL;DR: The concept of urban computing is introduced, discussing its general framework and key challenges from the perspective of computer sciences, and the typical technologies that are needed in urban computing are summarized into four folds.
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Models and algorithms for road network design: a review and some new developments
Hai Yang,Michael G.H. Bell +1 more
TL;DR: The elasticity of travel demand is incorporated into the NDP and the economic‐based objective function for optimization is sought and the mixed network design problem involving simultaneous choice of link addition and capacity improvement is posed.
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Capacity reliability of a road network: an assessment methodology and numerical results
TL;DR: The capacity reliability analysis is extended by providing a comprehensive methodology, which combines reliability and uncertainty analysis, network equilibrium models, sensitivity analysis of equilibrium network flow and expected performance measure, as well as Monte Carlo methods, to assess the performance of a degradable road network.
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Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach
TL;DR: This paper is one of the first DL studies to forecast the short-term passenger demand of an on-demand ride service platform by examining the spatio-temporal correlations and the FCL-Net achieves the better predictive performance than traditional approaches.
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Alternating Direction Method with Self-Adaptive Penalty Parameters for Monotone Variational Inequalities
TL;DR: This paper presents a modified alternating direction method that adjusts the penalty parameter per iteration based on the iterate message and preliminary numerical tests show that the self-adaptive adjustment technique is effective in practice.