Reveal non-linear system coupling network with information theory

Haoyun Tang

doi:10.1117/12.2631124

18 March 2022 Reveal non-linear system coupling network with information theory

Haoyun Tang

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121681V (2022) https://doi.org/10.1117/12.2631124
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

In a complex system, the strength and direction of feedback among different agents are difficult to quantified, especially due to the non-linearity. To quantitively estimate the coupling network of complex system, multiple statistical approaches have been widely adopted, including e.g., pairwise correlative analysis, Granger causality analysis. However, these analytic approaches often assume linear system and relative simple coupling pattern. In this work, I employed the concept of information entropy transfer and explore the non-linear interactions of near surface water and energy. This way could acutely find weak coupling effect of data and construct a chart of overview which can reflect the coupling impacts between variables directly. The goal of the analysis is to gain results about how energy circulate in the environment on the earth. Change in ways energetic transfer may imperil the survival of living matters on the path.I found that 1)From 1850 to 2005 the influences of existing variables other than the coupling relationship between precipitation(pr) and latent heat(hfls) are weak. 2)From the predictive model between 2006 and 2100,the effecting strength becomes relatively moderate and concordant.3)The time lag to surface temperature become affected by 3 variables(solar radiation,latent heat and sensitive heat) covering a whole year in the period between 2006 and 2100 in comparison with the other period with 2 variables(sensitive heat and latent heat) in the same month.

Citation Download Citation

Haoyun Tang "Reveal non-linear system coupling network with information theory", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121681V (18 March 2022); https://doi.org/10.1117/12.2631124

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KEYWORDS

Complex systems

Data modeling

Climatology

Heat flux

Information theory

Statistical analysis

Climate change

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