Research on robustness of R&D network under cascading propagation of risk with gray attack information
Research on robustness of R&D network under cascading propagation of risk with gray attack information
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DOI：
10.1016/j.ress.2013.03.009
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发表时间：
2013-09
期刊：
影响因子：
--
通讯作者：
Yanlu Zhang;Naiding Yang
中科院分区：
文献类型：
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作者：
Yanlu Zhang;Naiding Yang
针对研发网络中风险的级联传播现象和攻击信息的不精确性，本文构建了基于灰色攻击信息的风险级联传播模型。该模型以节点度描述的灰色攻击信息通过负偏差和正偏差来衡量，并提出抗风险临界阈值作为研发网络鲁棒性的新指标。然后通过数值模拟分析了带有灰色攻击信息的风险级联传播下研发网络的鲁棒性。结果表明，R&D网络在随机攻击下鲁棒性最强，在故意攻击下鲁棒性最弱；研发网络的鲁棒性随着攻击信息偏差的增加而增强，当所有企业的能力分布异构时，这一点变得更加显着；随着各企业能力分布异质性的增加，研发网络在一次攻击下的鲁棒性下降；研发网络的鲁棒性对攻击信息的负偏差比对正偏差更敏感。该研究工作将为今后研发网络中的级联传播防控提供理论依据。
Facing the cascading propagation phenomenon of risk in R&D network and the imprecision of attack information, this paper builds the cascading propagation model of risk with gray attack information. In this model, gray attack information described by node degree is measured by negative and positive deviations, and the critical threshold of resisting risk is also proposed as a new indicator of robustness of R&D network. Then the paper analyzes the robustness of R&D network under cascading propagation of risk with gray attack information through numerical simulation. The results show that R&D network has the strongest robustness under random attack, but has the weakest one under intentional attack; robustness of R&D network increases with the increase of deviation from attack information, which becomes increasingly significant when all enterprises' capacities distribution is heterogeneous; robustness of R&D network under one attack decreases with the increasing heterogeneity of all enterprises' capacities distribution; robustness of R&D network is more sensitive to the negative deviation than to the positive deviation from attack information. This research work will provide a theoretical basis for preventing and controlling cascading propagation in R&D network in the future.