为了考察不同增长模式下知识网络的拓扑结构及知识节点的历时老化,建立了知识网络的增长模型.模型采用了泛增长函数的方式进行了一般的分析.数理分析和模拟仿真发现:当知识增长率为线性等收敛函数时,知识网络的度分布与增长模式无关,且知识节点的历时被引是一直衰减的;而当增长率函数为发散性的指数函数时,知识节点的度分布指数较前者要小,节点的历时被引数则是单调上升的;增长速度越快,指数增长模式具有越平坦的度分布,知识的利用率越高,相反,收敛性的线性增长等在知识利用上分化则相对更大,知识利用率相对低些.%For the analysis of topology and ohsolescence of knowledge under different growth patterns, we constructed an evolution model of knowledge networks. A general function analysis and simulation had been done, it was found that the degree distribution had no relation to the growth pattern and the diachronic citation of vertex decreased, when the growth ratio of knowledge was convergence function, such as liner function; On the other hand, the exponent of degree distribution was small and the diachronic citation was increased when the growth function was transpire function, like exponent function. The faster the rapid of growth , the flatter the degree distribution it was, which also means the higher efficiency of knowledge utilization.
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