论文标题
部分可观测时空混沌系统的无模型预测
Power Network Uniqueness and Synchronization Stability from a Higher-order Structure Perspective
论文作者
论文摘要
三元子图分析揭示了基于高阶连接模式的功率网络中的结构特征。与无标度，小世界和随机网络相比，功率网络具有五个单向三元子图的独特三合会显着性概况（TSP）。值得注意的是，三合会的封闭在电力网络中具有最高的意义。因此，唯一的TSP可以用作区分功率网络与其他复杂网络的结构标识符。电力网络构成网络超家族。此外，基于随机增长模型的合成功率网络长大为属于超家族的网络，传输线数量少。三元封闭的重要性与通过网络冗余所测量的施工成本密切相关。同步稳定性与施工成本之间的权衡导致电力网络超家族。以独特的TSP为特征的电力网络本质上是权衡的结果。电力网络超家族的独特性讲述了一个重要的事实，即电力网络。
Triadic subgraph analysis reveals the structural features in power networks based on higher-order connectivity patterns. Power networks have a unique triad significance profile (TSP) of the five unidirectional triadic subgraphs in comparison with the scale-free, small-world and random networks. Notably, the triadic closure has the highest significance in power networks. Thus, the unique TSP can serve as a structural identifier to differentiate power networks from other complex networks. Power networks form a network superfamily. Furthermore, synthetic power networks based on the random growth model grow up to be networks belonging to the superfamily with a fewer number of transmission lines. The significance of triadic closures strongly correlates with the construction cost measured by network redundancy. The trade off between the synchronization stability and the construction cost leads to the power network superfamily. The power network characterized by the unique TSP is the consequence of the trade-off essentially. The uniqueness of the power network superfamily tells an important fact that power networks.
