基于高斯函数拟合的多维数据三维可视化仿真  

3D Visual Simulation of Multidimensional Data Based on Gaussian function Fitting

作　　者：裴庆庆 刘慧慧 PEI Qing-qing;LIU Hui-hui(College of Information Engineering Zhengzhou University of Industrial Technology,Zhengzhou Henan 451150,China;College of Computer Science and Technology Henan Polytechnic University,Jiaozuo Henan 454002,China)

机构地区：[1]郑州工业应用技术学院信息工程学院,河南郑州451150 [2]河南理工大学计算机科学与技术学院,河南焦作454002

出　　处：《计算机仿真》2024年第1期206-210,共5页Computer Simulation

摘　　要：为了得到满意的多维数据可视化效果,提出一种基于四叉树的多维数据三维可视化方法。采用随机森林和转导推理相结合的方式提取多维数据特征,通过四叉树对多维数据特征简化处理,降低数据处理难度。将简化处理后的多维数据特征点作为热点,利用高斯函数拟合计算各个热点对周围数据产生的作用值,将全部热点的作用值累加,将累加值作为最终的热度值,采用光线投射方法展开三维图绘制,最终实现多维数据三维可视化。经实验测试证明,采用所提方法可以有效提升多维数据三维可视化效果的分辨率,减少内存损耗,提升执行效率。In order to obtain a satisfactory multi-dimensional data visualization effect,this paper proposed a 3D visualization method for multi-dimensional data based on quadtrees.Firstly,we combined the random forest with transduction inference to extract multi-dimensional data features.Through the quadtree,we simplified the multi-dimensional data features,thereby reducing the difficulty of data processing.Then,we took the simplified features as hotspots and used Gaussian functions to fit and calculate the effect of each hotspot on the surrounding data.After that,we accumulated the effect values of all hotspots and used them as the final heat value.Finally,we adopted the ray-casting algorithm to draw the three-dimensional map,thus realizing the three-dimensional visualization of multidimensional data.Experimental results prove that the proposed method can effectively improve the resolution of threedimensional visualization effect,reduce memory loss,and increase execution efficiency.

关 键 词：特征提取 四叉树 多维数据 三维可视化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]