中文标题#
基于队列的数据显示的二维时间序列方法增强预测
英文标题#
Enhancing Forecasting with a 2D Time Series Approach for Cohort-Based Data
中文摘要#
本文介绍了一种新颖的二维（2D）时间序列预测模型，该模型整合了随时间变化的群体行为，解决了小数据环境中的挑战。 我们使用多个真实世界的数据集证明了其有效性，展示了在准确性和适应性方面优于参考模型的表现。 该方法为面临财务和营销预测挑战的行业提供了有价值的见解，以支持战略决策。
英文摘要#
This paper introduces a novel two-dimensional (2D) time series forecasting model that integrates cohort behavior over time, addressing challenges in small data environments. We demonstrate its efficacy using multiple real-world datasets, showcasing superior performance in accuracy and adaptability compared to reference models. The approach offers valuable insights for strategic decision-making across industries facing financial and marketing forecasting challenges.
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