Simulation Research on Evolving Model of Knowledge Network

A new type of knowledge network evolving model which comprises node addition and node deletion with the concept of local world preferential connection mechanism based on knowledge correlation degree and preferential deletion mechanism is studied.A series of numerical simulations of the cumulative degree distribution of the knowledge networks are conducted.The cumulative degree distribution at first has the property of scale-free approximately,and then it turns into an exponential truncation.Finally some knowledge indices generated by different connection and deletion mechanisms are compared.The results of simulations show that knowledge-based local world preferential connection mechanism and degree-based preferential deletion mechanism are prone to arousing heterogeneity and improving performance of the network comparing to the random local world preferential connection mechanism and random preferential deletion mechanism,which are advantageous to network formation.