A commodity distribution management method and system based on big data analysis
By using multi-dimensional data preprocessing and Transformer model sales forecasting, combined with distribution network graph structure and dynamic graph neural network optimization, the optimal distribution plan is generated. This solves the problems of insufficient multi-dimensional data integration and dynamic adjustment capabilities of the distribution network in existing technologies, and achieves efficient and flexible distribution management.
CN119539866BActive Publication Date: 2025-11-25ZHEJIANG PISTACHIO SHUZHI TECH CO LTD
Patent Information
- Application Number
- CN202510095907.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-22
- Publication Date
- 2025-11-25
- Estimated Expiration
- 2045-01-22
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Figure CN119539866B_ABST
Abstract
The application discloses a kind of commodity distribution management method and system based on big data analysis, it is related to intelligent distribution management technical field, including, collection multidimensional data, and multidimensional data pre-processing;Based on Transformer model, construct sales forecast model, input multidimensional data after pre-processing into sales forecast model, obtain sales terminal predicted sales;Based on sales terminal predicted sales, construct distribution network graph structure;Based on distribution network graph structure, obtain distribution scheme by dynamic graph neural network;Through multi-objective optimization, distribution scheme is dynamically adjusted, and optimal distribution scheme is generated;Based on optimal distribution scheme, through regional adaptive optimization, regional distribution scheme is customized.The application is integrated and pre-processed by multidimensional data, based on Transformer model's sales forecast, the dynamic optimization of distribution network graph and the optimal distribution scheme generation of multi-objective optimization, significantly improve distribution efficiency, flexibility and accuracy.
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Citation Information
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