The application of machine learning in solar physics has the potential to greatly enhance our understanding of the complex processes that take place in the atmosphere of the Sun. By using techniques such as deep learning, we are now in the position to analyze large amounts of data from solar observations and identify patterns and trends that may not have been apparent using traditional methods. This can help us improve our understanding of explosive events like solar flares, which can have a strong effect on the Earth environment. Predicting hazardous events on Earth becomes crucial for our technological society. Machine learning can also improve our understanding of the inner workings of the sun itself by allowing us to go deeper into the data and to propose more complex models to explain them. Additionally, the use of machine learning can help to automate the analysis of solar data, reducing the need for manual labor and increasing the efficiency of research in this field.

机器学习在太阳物理学中的应用有可能极大地增强我们对太阳大气中发生的复杂过程的理解。通过使用深度学习等技术，我们现在能够分析来自太阳观测的大量数据，并识别使用传统方法可能不明显的模式和趋势。这可以帮助我们提高对太阳耀斑等爆炸事件的了解，这些事件会对地球环境产生强烈影响。预测地球上的危险事件对于我们的技术社会至关重要。机器学习还可以让我们更深入地研究数据并提出更复杂的模型来解释它们，从而提高我们对太阳本身内部运作的理解。此外，机器学习的使用可以帮助自动分析太阳能数据，减少对体力劳动的需求并提高该领域的研究效率。