Health assessment method of regional power grid topology based on deep neural network

Jiang, Yuan; Xu, Duohong; Cheng, Li; Zhang, Bei; Cui, Yanni; Hu, Hongxia; Liu, Jingzhong

doi:10.1117/12.2637637

Cited by 1 publication

(1 citation statement)

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“…Each segmentation of KD tree will divide point cloud data into two halves through hyperplane, and 2 1 non-leaf nodes and 2 leaf nodes can be generated after n segmentation. Cheng pointed out that in uniform mesh segmentation method, the total number of point clouds is N, and each mesh contains [√𝑁] points, which is the best choice [10]. When the data are evenly distributed, the segmentation effect of KD tree can be similar to that of uniform raster segmentation method, so K= [√𝑁]can be used as the basis of the segmentation stop condition.…”

Section: 1kd Tree Segmentation Stop Conditionmentioning

confidence: 99%

Optimization of 3D GIS model reconstruction algorithm based on laser point clouds

Liu

Niu

2023

International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022)

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As the data basis of 3D geographic information service, 3D model is widely used in 3D terrain visualization, smart city, geological monitoring and other fields. 3D laser point clouds have become one of the main data sources for 3D GIS modeling due to their high precision and fast modeling. When researchers mesh laser point clouds and generate some elongated triangles due to the rule constraints of the algorithm itself, elongated triangles can cause the burden of mesh optimization, affecting the efficiency of mesh reconstruction. In this paper, based on the incremental insertion algorithm, we mitigate the adverse effects of elongated triangles by constructing a non-fully partitioned KD tree index and introducing control points to influence the insertion order of point clouds. We use the proposed algorithm, BRIO and KD tree algorithms to reconstruct Bunny and Horse. We found that the proposed algorithm is superior to the other two algorithms in time efficiency and can suppress the appearance of elongated triangles well.

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Section: 1kd Tree Segmentation Stop Conditionmentioning

confidence: 99%