What is it about?
In addressing the limitations of traditional measurement methods and providing a more comprehensive and accurate assessment of industrial technology security, this research presents an approach based on a discrete Hopfield Neural Network (HNN) for evaluating industrial technology security in international trade.
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Why is it important?
The results indicate an overall upward trend in security in China's international trade industry. Within this trend, the research observes a stepwise increase in scale components, leading to continuous improvement in security. In terms of quality components, although security develops relatively slowly overall, it exhibits a trend of initial gradual decline followed by rapid growth.
Perspectives
This research outcome provides substantial support for the research of industrial technology in international trade. The proposed method can assist businesses in evaluating their technological security in international trade and offer robust support for international trade decision-making.
furong huang
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This page is a summary of: Industrial technology network security measurement in international trade under discrete hopfield neural network, Journal of Computational Methods in Sciences and Engineering, May 2024, IOS Press,
DOI: 10.3233/jcm-237128.
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