应用于天气预报的机器学习

S. E. Haupt, J. Cowie, Seth Linden, Tyler C. McCandless, B. Kosović, S. Alessandrini
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引用次数: 28

摘要

美国国家大气研究中心(NCAR)在将机器学习应用于天气预报挑战方面有着悠久的历史。动态综合预报(DICast®)系统是最早的自动天气预报引擎之一。它现在在相当多的公司使用,有许多应用程序。NCAR正在完成的一些应用包括DICast和其他人工智能技术,包括可再生能源、地面运输和野火预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning for Applied Weather Prediction
The National Center for Atmospheric Research (NCAR) has a long history of applying machine learning to weather forecasting challenges. The Dynamic Integrated foreCasting (DICast®) System was one of the first automated weather forecasting engines. It is now in use in quite a few companies with many applications. Some applications being accomplished at NCAR that include DICast and other artificial intelligence technologies include renewable energy, surface transportation, and wildland fire forecasting.
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