Research on E-commerce product demand forecast and inventory optimization based on improved network optimization model
Keywords:
E-Commerce Platform; Demand Forecast; Inventory Optimization; Probability Density Clustering; SBO-LSTM Neural NetworkAbstract
This study aims to accurately predict the future demand for goods on e-commerce platforms and optimize inventory through an improved network optimization model. First, take merchants, warehouses, and commodities as dimensions and build a probability density cluster analysis model based on time series to determine the classification of commodities under the most similar characteristics. Then, using the shipment volume as the dependent variable and the clustering correlation factors as the independent variables, an SBO-LSTM neural network model was constructed to optimize the shipment volume prediction. Through training and testing, the model shows high accuracy and stability. Finally, the trained model is applied to the data of each merchant in each warehouse, and the commodity demand forecast value from 2023-05-16 to 2023-05-30 is output, providing optimal demand forecast and inventory strategy for each merchant. The research results show that when the merchant number is 6 and the warehouse number is 43, the forecast value of product demand in the first three days is 2, 2, and 3.
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APA:
Meng, X., Zhao, Q., & Bi, Y. (2024). Research on e-commerce product demand forecast and inventory optimization based on improved network optimization model. International Scientific Technical and Economic Research, 2(1), 52–60. http://www.istaer.online/index.php/Home/article/view/No.2405
GB/T 7714-2015:
Meng Xiangjun, Zhao Qian, Bi Yingxi. Research on e-commerce product demand forecast and inventory optimization based on improved network optimization model[J]. International Scientific Technical and Economic Research, 2024, 2(1): 52–60. http://www.istaer.online/index.php/Home/article/view/No.2405
MLA:
Meng, Xiangjun, Qian Zhao, and Yingxi Bi. "Research on e-commerce product demand forecast and inventory optimization based on improved network optimization model." International Scientific Technical and Economic Research, 2.1 (2024): 52-60. http://www.istaer.online/index.php/Home/article/view/No.2405
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