Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (9): 220-223.DOI: 10.3778/j.issn.1002-8331.2010.09.063

• 工程与应用 • Previous Articles     Next Articles

Visualization of multi-dimensional data with interpolation based on compactly supported radial basis functions

TAN Ye-hao,JIANG Zhi-fang,DU Xiao-liang,MENG Xiang-xu   

  1. School of Computer Science and Technology,Shandong University,Jinan 250101,China
  • Received:2008-09-23 Revised:2008-12-25 Online:2010-03-21 Published:2010-03-21
  • Contact: TAN Ye-hao



  1. 山东大学 计算机科学与技术学院,济南 250101
  • 通讯作者: 谭业浩

Abstract: This paper analyzes the organization structure for numerical forecasting data of the city air quality in space and in time,and constructs an overall frame for the multi-dimensional space data.The superiority and insufficiency are elaborated for several kinds of interpolation methods.Based on comparison,it has introduced the method of partial radial direction interpolation based on compactly supported radial basis functions into manage of multi-dimensional data.By the partial interpolation in the space dimension and in the time dimension,it has realized the restructuring of the multi-dimensional data.And it has realized the dynamic visualization in three dimensions for large-scale forecasting data of air quality based on the new multi-thread method with encapsulation of call-back functions.Experimental results demonstrate that the above method can satisfy the actual need of quality and the operating speed regarding large-scale data’s visualization aspect.

Key words: compactly supported radial basis functions, multi-dimensional space, encapsulation, call-back function

摘要: 通过分析某城市空气质量数值预报数据的时空组织结构,构建出了多维空间数据的整体框架。论述了几种插值方法的优缺点,在比较的基础上,将新的紧支径向基函数局部径向点插值方法引入到多维数据处理中,在空间、时间维度上对数据进行局部插值,从而实现数据的重构。以新的基于封装回调函数的多线程方法实现了大规模空气质量预报数据的三维动态可视化。实验结果表明,以上方法应用于大规模数据可视化时,其质量和运算速度都能满足实际需要。

关键词: 紧支径向基函数, 多维空间, 封装, 回调函数

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