تقرير
Machine learning for Earth System Science (ESS): A survey, status and future directions for South Asia
العنوان: | Machine learning for Earth System Science (ESS): A survey, status and future directions for South Asia |
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المؤلفون: | Singh, Manmeet, Kumar, Bipin, Chattopadhyay, Rajib, Amarjyothi, K, Sutar, Anup K, Roy, Sukanta, Rao, Suryachandra A, Nanjundiah, Ravi S. |
سنة النشر: | 2021 |
المجموعة: | Computer Science Physics (Other) |
مصطلحات موضوعية: | Computer Science - Machine Learning, Physics - Atmospheric and Oceanic Physics |
الوصف: | This survey focuses on the current problems in Earth systems science where machine learning algorithms can be applied. It provides an overview of previous work, ongoing work at the Ministry of Earth Sciences, Gov. of India, and future applications of ML algorithms to some significant earth science problems. We provide a comparison of previous work with this survey, a mind map of multidimensional areas related to machine learning and a Gartner's hype cycle for machine learning in Earth system science (ESS). We mainly focus on the critical components in Earth Sciences, including atmospheric, Ocean, Seismology, and biosphere, and cover AI/ML applications to statistical downscaling and forecasting problems. |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2112.12966 |
رقم الأكسشن: | edsarx.2112.12966 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |