4 papers
Gaussian Linear Functional Manifold Method for Massive Point Cloud Data
Hong Zhao, Tonglin Zhang, Baijian Yang +2
Reconstructing continuous terrain manifolds from massive, unstructured airborne LiDAR point clouds remains challenging in complex Wildland-Urban Interface (WUI) environments, where…
Dual-Head Physics-Informed Graph Decision Transformer for Distribution System Restoration
Hong Zhao, Jin Wei-Kocsis, Adel Heidari Akhijahani +1
Driven by recent advances in sensing and computing, deep reinforcement learning (DRL) technologies have shown great potential for addressing distribution system restoration (DSR) u…
Unsupervised Machine Learning for Detecting and Locating Human-Made Objects in 3D Point Cloud
Hong Zhao, Huyunting Huang, Tonglin Zhang +3
A 3D point cloud is an unstructured, sparse, and irregular dataset, typically collected by airborne LiDAR systems over a geological region. Laser pulses emitted from these systems…
Exploring a Physics-Informed Decision Transformer for Distribution System Restoration: Methodology and Performance Analysis
Hong Zhao, Jin Wei-Kocsis, Adel Heidari Akhijahani +1
Driven by advancements in sensing and computing, deep reinforcement learning (DRL)-based methods have demonstrated significant potential in effectively tackling distribution system…