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End date: 2024 × Start date: 2020 × Start date: 2000 × DDC: 530 × Has files: Yes × Type: Text × Publisher: Bristol : Institute of Physics Publishing × Subject: Complex networks × Subject: Weighted complex networks ×

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    Detours around basin stability in power networks
    (Bristol : Institute of Physics Publishing, 2014) Schultz, P.; Heitzig, J.; Kurths, J.
    To analyse the relationship between stability against large perturbations and topological properties of a power transmission grid, we employ a statistical analysis of a large ensemble of synthetic power grids, looking for significant statistical relationships between the single-node basin stability measure and classical as well as tailormade weighted network characteristics. This method enables us to predict poor values of single-node basin stability for a large extent of the nodes, offering a node-wise stability estimation at low computational cost. Further, we analyse the particular function of certain network motifs to promote or degrade the stability of the system. Here we uncover the impact of so-called detour motifs on the appearance of nodes with a poor stability score and discuss the implications for power grid design.
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    Characterizing time series: When Granger causality triggers complex networks
    (Bristol : Institute of Physics Publishing, 2012) Ge, T.; Cui, Y.; Lin, W.; Kurths, J.; Liu, C.
    In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH 7 human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.