Attachment mechanisms which construct connections from old knowledge vertex to new one is the mostimportant factor to form the topological structure of knowledge network. This paper constructed the evolution model by introducing preferential attachment of degree and time. The model considered the changing of edges and time effect to the attachment. By function analysis and simulation, it found that it had flatter degree distribution in liner growth edge attachment, and time effect made new knowledge more used, restraining the defect of Matthew effect.%新旧知识节点之间前承后继的连接机制是知识网络拓扑结构形成的最关键部分,通过引入度优先连接、时间优先连接,构造了知识网路的演化模型.模型考虑了知识节点出度的动态变化以及时间效应的作用,数理分析及仿真实验发现:出度线性增长形成更平坦的度分布,而出度对数增长对度分布影响不大,出度对数增长更加符合现实情况;时间效应使得新近加入知识节点也获得了较多的利用,自动平抑了马太效应的负面影响.
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