Abstract: Extracting ground points from LiDAR point clouds is essential for constructing digital terrain models (DTMs). This article presents a filtering method with strip curve fitting, based on the ...
Abstract: Landslide susceptibility mapping (LSM) is of great significance for regional land resource planning and disaster prevention and reduction. The machine learning (ML) method has been widely ...
Abstract: This paper presents a new method for enhancing Alternating Current Power Flow (ACPF) analysis. The method integrates the Newton-Raphson (NR) method with Enhanced-Gradient Descent (GD) and ...
Abstract: This paper presents a novel feature update method that leverages the relationships among batch elements, addressing scenarios both with and without an external graph. In the absence of an ...
Abstract: Biological and biomedical knowledge graphs can be disparate in their design when a standard has not been widely accepted by the community, even more when they represent data from a ...
Abstract: Factor graphs have demonstrated remarkable efficiency for robotic perception tasks, particularly in localization and mapping applications. However, their application to optimal control ...
Abstract: The data-driven methods based on the graph convolution architecture provide a promising direction for accelerating power flow (PF) calculation. These methods directly predict operational ...
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