Application of an Improved Link Prediction Algorithm Based on Complex Network in Industrial Structure Adjustment

Abstract

For a healthy industrial structure (IS) and stable economic development in China, this study proposes an improved link prediction algorithm (LP) based on complex networks. The algorithm calculates the similarity by constructing a mixed similarity index. A regional IS network model is built in the study, and the direction of IS adjustment is calculated with the mixed similarity indicators. In this study, the prediction accuracy of the proposed improved LP algorithm in the real network dataset is up to 0.944, which is significantly higher than that of the other algorithms. In the reality of IS optimization, industries of high similarity could be obtained through similarity algorithms, and reasonable coordinated development strategies are proposed. In addition, the simulated IS adjustment strategy in this study shows that it is highly sustainable in development, which is reflected in its lower carbon emissions. The optimization of IS adjustment could be achieved through IS network model and the improved LP algorithm. This study provides valuable suggestions for China’s regional industrial structure adjustment.

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