电商驱动下的快递业务量预测研究

Research on Express Delivery Volume Prediction Driven by E-Commerce

摘要: 随着电子商务的持续渗透，快递业务量已成为反映经济活动的重要指标之一。对其进行精准预测，对物流公司的资源配置、运力规划乃至整个供应链的效率提升都至关重要。本文研究的创新性主要体现在将Attention-BiLSTM这一混合深度学习模型应用于省级快递业务量预测。相比于传统的统计学模型，该模型理论上能够更好地捕捉时间序列中的长期依赖关系、非线性模式以及关键时间节点的影响，具有一定的技术前沿性。

Abstract: With the continuous penetration of e-commerce, the volume of express delivery has become a key indicator reflecting economic activity. Accurate forecasting of this volume is crucial for logistics companies in resource allocation, transport capacity planning, and even enhancing overall supply chain efficiency. The innovation of this study lies in its application of the Attention-BiLSTM hybrid deep learning model to forecast express delivery volume at the provincial level. Compared to traditional statistical models, this model theoretically excels in capturing long-term dependencies, non-linear patterns, and the impact of critical time points in time series data, demonstrating a degree of technological advancement.