Sustainable economic growth is closely linked to synergy in a national system of innovation. Although the dynamic synergy mechanism of the triple helix relations is essential to technology innovation, there are limited research methodologies to study or estimate the synergy effect accurately. This paper introduces a new approach in non-linear complex systems theory to offer steps towards a possible solution to this conundrum. Based on the pattern formation of the Belousov-Zhabotinsky's

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... the paper constructs a simulation equation to explore the evolution mechanism by comparing the ideal state with the current state in China. The research finds that (1) under the ideal balanced condition of industrial absorptive capacity and academic knowledge transfer capability, the stronger incentive policies would play much more important roles than weak policies; (2) the performance of collaborative innovation is not optimal under current situation in China, but the industrial absorptive capacity, especially in private enterprises, has exceeded the capability of knowledge transfer in academia, and it has become the main driving force to promote future innovation. If the innovation policy can be focused on the high-level balance between the knowledge network and innovation network to promote synergy in China, the innovation performance will be accelerated more efficiently.