Analysis method and system oriented to regional industry network evolution and related equipment

By constructing an enterprise information database and growth trend prediction model, combining machine learning models and link prediction methods, the problem of lack of quantitative support for industrial network evolution trend analysis in the existing technology is solved, and more accurate and scientific industrial network evolution prediction is achieved.

CN119692570AActive Publication Date: 2025-03-25UNIV OF SCI & TECH OF CHINA
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Patent Information

Application Number
CN202510206678.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-25
Publication Date
2025-03-25
Estimated Expiration
2045-02-25

AI Technical Summary

Technical Problem

The existing technology lacks quantitative support when analyzing the evolution trend of industrial networks and lacks dynamic analysis capabilities, resulting in limited support for regional industrial management departments.

Method used

By obtaining enterprise registration information, business activities and external environment data, building an enterprise information database, extracting enterprise growth timing data from different industries, building a growth trend prediction model, and using XGBOOST and LightGBM models to predict the risk of enterprise demise, and combining link prediction methods to predict industrial network evolution.

Benefits of technology

It realizes dynamic quantitative analysis of industrial network evolution trends, improves the accuracy and robustness of predictions, and provides more scientific analysis results and more universal decision-making support.

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Abstract

The invention discloses an analysis method and system oriented to regional industry network evolution and related equipment. The analysis method comprises the following steps: constructing an enterprise information database oriented to specific regional industry network evolution analysis; sequentially extracting enterprise growth time sequence data of different industries in the region based on the enterprise information database, and constructing a growth situation prediction model of the regional sub-industries to predict the enterprise growth amount of different industries in the specific region in the future; an enterprise relationship network is constructed based on an enterprise information database, enterprises with high extinction risks are removed, potential relationships among residual nodes are predicted through a link prediction method based on the nodes and relationships of the residual industrial network, and industrial network evolution prediction is realized in combination with enterprise growth amounts of different industries. The time sequence similarity is adopted to improve an industrial development trend prediction model, so that the error of short-term prediction can be effectively reduced, and the prediction of a long-term growth trend can be ensured; and multi-dimensional enterprise related data is adopted, so that the analysis result is more scientific.
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