中文标题#
基於隊列的數據顯示的二維時間序列方法增強預測
英文标题#
Enhancing Forecasting with a 2D Time Series Approach for Cohort-Based Data
中文摘要#
本文介紹了一種新穎的二維（2D）時間序列預測模型，該模型整合了隨時間變化的群體行為，解決了小數據環境中的挑戰。我們使用多個真實世界的數據集證明了其有效性，展示了在準確性和適應性方面優於參考模型的表現。該方法為面臨財務和行銷預測挑戰的行業提供了有價值的見解，以支持戰略決策。
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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