论文标题
COVID-19趋势预测的深度学习方法
A Deep Learning Approach for COVID-19 Trend Prediction
论文作者
论文摘要
在这项工作中，我们开发了一种基于深度学习模型的方法，以预测美国SARS-COV-2的传播趋势。我们使用美国实施了设计的模型来确认案例和州人口统计数据，并获得了有希望的趋势预测结果。该模型通过封闭的复发单位结构结合了人口统计信息和流行时序数据。最终提供了主导人口统计因素的识别。
In this work, we developed a deep learning model-based approach to forecast the spreading trend of SARS-CoV-2 in the United States. We implemented the designed model using the United States to confirm cases and state demographic data and achieved promising trend prediction results. The model incorporates demographic information and epidemic time-series data through a Gated Recurrent Unit structure. The identification of dominating demographic factors is delivered in the end.
