山东大学学报 (工学版) ›› 2026, Vol. 56 ›› Issue (2): 35-42.doi: 10.6040/j.issn.1672-3961.0.2024.225
• 机器学习与数据挖掘 • 上一篇
张水旺,杨晨*,宗启东,胡钢
ZHANG Shuiwang, YANG Chen*, ZONG Qidong, HU Gang
摘要: 为了克服多数传统方法在复杂网络关键节点识别中单一指标和赋权主观性的问题,提出一种基于VIKOR-GRA模型的关键节点识别方法VGKNI(VIKOR-GRA-Key node identification)。采用熵权法与灰色关联分析,在传统中心性指标选取的基础上,引入桥中心性指标;基于多个真实网络数据集验证本研究算法,与其他多种方法对比分析。结果表明,本研究方法所得关键节点排名合理,单调性及模拟恢复效果较部分传统方法更优。本研究方法具有处理复杂网络关键节点识别问题的优势,为复杂网络研究提供新的视角与思路。
中图分类号:
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