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Kriging interpolation algorithm based on constraint particle swarm optimization

JIA Yu;DENG Shi-wu;YAO Xing-miao;CAI Yuan-fei;Institute of Nuclear Technology and Automation Engineering,Chengdu University of Technology;School of Communication and Information Engineering,University of Electronic Science and Technology of China;  
According to the deficiency of the conventional Kriging interpolation algorithm,this paper proposes an improved interpolation method,that is,the Kriging interpolation algorithm based on the constraint particle swarm optimization(PSO)by changing the diversity of the particles in the PSO and combined with the characteristics of the geological variables and the data features.This method improves the precision of interpolation by means of Gaussian variation,setting the weight coefficient of sample points and limiting the search scope in the process of PSO.The experiment result indicates that the Kriging interpolation algorithm based on the constraint PSO can obtain a high-precision interpolation result superior to that of the conventional Kriging interpolation algorithm.
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