3D Visual Simulation of Multidimensional Data Based on Gaussian function Fitting
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-di-mensional 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 multi-dimensional data.Experimental results prove that the proposed method can effectively improve the resolution of three-dimensional visualization effect,reduce memory loss,and increase execution efficiency.
NETL
NSTL
万方数据
维普
