标题： 基于改进的Transformer网络增强热带气旋路径预报 显示英文标题

标题： Enhancing Tropical Cyclone Path Forecasting with an Improved Transformer Network

摘要： 风暴是一种极端天气。 因此，预测风暴的路径对于保护人类生命和财产极其重要。 然而，由于风暴轨迹经常变化，风暴预报非常具有挑战性。 在本研究中，我们提出了一种改进的深度学习方法，使用Transformer网络来预测未来6小时内风暴的移动轨迹。 用于训练模型的风暴数据来自美国国家海洋和大气管理局（NOAA）[1]。 仿真结果显示，所提出的方法比传统方法更准确。 此外，所提出的方法更快且更具成本效益。 显示英文摘要

摘要： A storm is a type of extreme weather. Therefore, forecasting the path of a storm is extremely important for protecting human life and property. However, storm forecasting is very challenging because storm trajectories frequently change. In this study, we propose an improved deep learning method using a Transformer network to predict the movement trajectory of a storm over the next 6 hours. The storm data used to train the model was obtained from the National Oceanic and Atmospheric Administration (NOAA) [1]. Simulation results show that the proposed method is more accurate than traditional methods. Moreover, the proposed method is faster and more cost-effective