Research on Evolution Analysis and Link Prediction of Green Innovation Cooperation Network

This paper is concerned with analyzing the evolution of green innovation collaborative network in Beijing- Tianjin-Hebei region and finding the unknown cooperative relationship by using the complex network and link prediction theory. Based on the Green Patent Cooperation data of Beijing- Tianjin-Hebei region from 2009 to 2020, this paper constructed cooperation networks and analyzed the evolution from three aspects: structure, centrality and clustering. Then used the link prediction theory to evaluate 14 prediction indexes to find the optimal link prediction algorithm of green innovation collaborative network, and explored the recommended cooperation in the innovation network, so as to put forward constructive suggestions for the coordinated development of green innovation in Beijing-Tianjin-Hebei region. The experimental results showed that the green patent cooperation network shows an overall growth trend, the structure evolves in a scale-free direction, and the cluster effect presents phased characteristics in the evolution process. In recent years, the centrality of core nodes has decreased slightly, and green innovation synergy has a diversified development trend. In the Beijing-Tianjin-Hebei green patent cooperation network, the link prediction accuracy using Katz index is the highest.