Home > Papers

 
 
Application of density-based sine cosine algorithm in soil moisture interpolation model
Li Gang 1,Li Ning 2 *,Chen Yuanzhi 2
1.School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876;School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876;School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876
2.
*Correspondence author
#Submitted by
Subject:
Funding: none
Opened online:12 December 2017
Accepted by: none
Citation: Li Gang,Li Ning,Chen Yuanzhi.Application of density-based sine cosine algorithm in soil moisture interpolation model[OL]. [12 December 2017] http://en.paper.edu.cn/en_releasepaper/content/4742360
 
 
Focused on the issue that sine cosine algorithm is easy to fall into local optimum in complex optimization problems, a density-based sine cosine algorithm was proposed. The algorithm combines the density information around the individual. In iterative process, individuals with higher density are far away from the center of density, making the algorithm not overcrowded during the exploration period, which enhances the local optimal avoidance ability of the algorithm. The standard function was used to test the performance of the algorithm, and the algorithm was applied to optimize the ordinary kriging interpolation model. The experimental data was from Changge, Henan Province. The results showed that the proposed algorithm had good convergence speed, better local optimal avoidance ability and better performance in optimizing soil moisture interpolation model .
Keywords:sine cosine algorithm; meta-heuristic algorithm; soil moisture interpolation model
 
 
 

For this paper
  • ● PDF (0B)
  • ● Revision 0 　　
  • ● Print this paper
  • ● Recommend this paper to a friend
  • ● Add to my favorite list

    Saved Papers

    Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags
Add yours

Related Papers
  • Other similar papers

Statistics
PDF Downloaded 23
Bookmarked 0
Recommend 0
Comments Array
Submit your papers