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Zhaobin Mo

As seen in: arXiv, MDPI, Cell Reports Physical Science, Games
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Articles by Zhaobin Mo

Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook

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By Xuân Di, Rongye Shi, Zhaobin Mo, Yongjie Fu
| MDPI
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by 1,2,*, 1,†, 1,† and 1 1 Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USA 2 Data Science Institute, Columbia University, New York, NY 10027, USA * Author to whom correspondence should be addressed. † These authors contributed equally to this work.
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Longitudinal Control Strategy for Connected Electric Vehicle with Regenerative Braking in Eco-Approach and Departure

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By Renato Galluzzi, Zhaobin Mo, Rolando Bautista-Montesano, Yongjie Fu
| MDPI
Abstract : The development of more sustainable urban transportation is prompting the need for better energy management techniques. Connected electric vehicles can take advantage of environmental information regarding the status of traffic lights. In this context, eco-approach and departure methods have been proposed in the literature. Integrating these methods with regenerative braking allows for safe, power-efficient navigation through intersections and crossroad layouts.
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Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook

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By Rongye Shi, Zhaobin Mo, Yongjie Fu
| arXiv
[Submitted on 3 Mar 2023 ( v1 ), last revised 1 Jul 2023 (this version, v2)] Title:Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook Download a PDF of the paper titled Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook, by Xuan Di and 3 other authors Download PDF Abstract: For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models),...
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Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection

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By Zhaobin Mo, Xuân Di, Rongye Shi
| MDPI
Author / Affiliation / Email Search Type Submit to this Journal Review for this Journal Edit a Special Issue Article Menu /ajax/scifeed/subscribe Altmetric share Share announcement Help format_quote Cite thumb_up ... Endorse textsms ... Comment Need Help? Support Find support for a specific problem in the support section of our website. Get Support Feedback Please let us know what you think of our products and services.
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Demonstrating stability within parallel connection as a basis for building large-scale battery systems

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By Zhe Li, Mu Lin, Anhao Zuo, Zhaobin Mo
| Cell Reports Physical Science Verified
Stability due to approach a stable closed orbit after cycles of charge and discharge Confronting the disturbing oscillations originating from the system’s intrinsic property, we have not made clear if they could trigger failures, such as divergence, instability, and poor robustness. Once these risks exist, the safety and controllability of battery systems will be seriously threatened.
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