Journal of System Simulation
Abstract
Abstract: Ocean data analysis is one of the important foundations in marine science research. Analysis on the sea surface temperature based on complex network theory helps explore the marine dynamics in a new perspective. The ocean is divided into grids, and the annual average of the sea surface temperature is calculated to reflect the properties of the corresponding grid area. The mutual information and the Pearson correlation coefficient are used to measure the similarity between different areas. The nonlinear and linear complex network models which reflect the station of the global marine climate can be built. Finally some popular measures including degree distribution, clustering coefficient and betweenness are introduced to discover the ocean phenomena, such as energy transfer of ocean, and the system robust and seasonal variation of the ocean dynamics are analyzed.
Recommended Citation
Xin, Sun; Li, Zhenhua; Dong, Junyu; Luo, Xinyan; and Yang, Yuting
(2019)
"Complex Network Modeling and Visualization Analysis for Ocean Observation Data,"
Journal of System Simulation: Vol. 30:
Iss.
7, Article 2.
DOI: 10.16182/j.issn1004731x.joss.201807002
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol30/iss7/2
First Page
2445
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201807002
Last Page
2452
CLC
TP391
Recommended Citation
Sun Xin, Li Zhenhua, Dong Junyu, LuoXinyan, Yang Yuting. Complex Network Modeling and Visualization Analysis for Ocean Observation Data[J]. Journal of System Simulation, 2018, 30(7): 2445-2452.
DOI
10.16182/j.issn1004731x.joss.201807002
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons