基于广义同步的分数阶复杂网络拓扑反演测试数据集

面向群智系统具有数目庞大，成员关系复杂等特点，通过找出行为特征一致的群智组织成员，并给出系统团队划分，从中观宏观尺度上找出群智系统的团队间关系，提出智能群体行为数据反演算法；从微观尺度上，提出有效的群智组织构架与系统参数反演算法。为了验证所提算法的有效性，基于数值仿真的方法，生成了本数据集，数据大小为40.2MB。

Given that crowd intelligence systems are characterized by a large number of members and complex member relationships, this study identifies crowd intelligence organization members with consistent behavioral characteristics, conducts team partitioning of the system, extracts inter-team relationships of the crowd intelligence system at meso and macro scales, and proposes an intelligent collective behavior data inversion algorithm. Furthermore, an effective crowd intelligence organization framework and system parameter inversion algorithm is proposed at the micro scale. To verify the effectiveness of the proposed algorithms, this dataset was generated via numerical simulation, with a data size of 40.2 MB.