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Fu Tan1,2, Xiaolong Chen2,3, Rui Chen2
1School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China.
本研究引入了一种使用Dempster-Shafer (DS) 证据理论的新方法,用于识别复杂网络中的有影响力的节点. DS方法有效地处理不确定性和多维数据,在网络分解任务中表现优于传统算法.
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