Ground air pollutants explanation based on multiple visibility graph of complex network by temporal community division.

ABSTRACT: In air pollution studies, the correlation analysis of environmental variables has usually been challenged by parametric diversity. Such variable variations are not only from the extrinsic meteorological conditions and industrial activities but also from the interactive influences between the multiple parameters. A promising solution has been motivated by the recent development of visibility graph (VG) on multi-variable data analysis, especially for the characterization of pollutants' correlation in the temporal domain, the multiple visibility graph (MVG) for nonlinear multivariate time series analysis has been verified effectively in different realistic scenarios. To comprehensively study the correlation between pollutant data and season, in this work, we propose a multi-layer complex netw

SUBMITTER: Guo C 

PROVIDER: S-EPMC10919876 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature