Rapid Display Method of Massive Data Based on Intelligent Clustering Model

In order to display three-dimensional massive data in real time,this paper proposes an improved rapid display algorithm for massive data.The CURE clustering algorithm is used to sort the data,and the data is indexed by Hilbert R-tree.The visual area prediction model predicts the next time visible ar...

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Bibliographic Details
Published in:Ji suan ji gong cheng Vol. 45; no. 8; pp. 53 - 59
Main Author: TANG Hongcheng, WEN Chang, FENG Wenxiang, XIE Kai, FANG Wenqing
Format: Journal Article
Language:Chinese
English
Published: Editorial Office of Computer Engineering 01.08.2019
Subjects:
massive data|hilbert r-tree|forecasting model|clustering algorithm|load in advance algorithm
ISSN:1000-3428
Online Access:Get full text
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Summary:In order to display three-dimensional massive data in real time,this paper proposes an improved rapid display algorithm for massive data.The CURE clustering algorithm is used to sort the data,and the data is indexed by Hilbert R-tree.The visual area prediction model predicts the next time visible area to realize rapid visualization of large amounts of data.Experimental results show that compared with the Visualization algorithm based on Motion of Viewpoint (VMV) and the Visualization algorithm based on Testing of Visibility (VTV),the rendering speed is 18.27% higher than the VMV algorithm without reducing the rendering quality.Compared with the VTV algorithm,the increase is 67.06%,the prediction area error rate is reduced by 9.73% compared with the VMV algorithm,and the VTV algorithm is reduced by 22.37%,which can quickly load data and accurately draw three-dimensional large data volume.
ISSN:1000-3428
DOI:10.19678/j.issn.1000-3428.0052493