A Hybrid Data-Knowledge Driven Method for Technology Development Risk Evaluation

As technology competition between countries and companies becomes increasingly intense, various commercial policy means are being used to hinder the development of competitors. The risk is thus much higher than before must be accurately assessed so that timely preventive measures can taken ensure safety development. In this paper, a hybrid data-knowledge driven method proposed for constructing evaluation indicator system identify high-risk technologies. Expert knowledge effectively leveraged through data-driven model developed from novel double-layer bagging machine learning method, which able learn aggregation rules in automatically. A case study on assessment smart chip-related technologies China provided. result, areas such as “field programmable gate array” “central processing unit” identified, manifesting effectiveness accuracy method.