Can I read Deep Learning-Based Weather Prediction: A Survey on EtoBox?
Deep Learning-Based Weather Prediction: A Survey by Xiaoli Ren; Xiaoyong Li; Kaijun Ren; Junqiang Song; Zichen Xu; Kefeng Deng; Xiang Wang is a Computer Science article available to read on EtoBox.
What is Deep Learning-Based Weather Prediction: A Survey about?
Weather forecasting plays a fundamental role in the early warning of weather impacts on various aspects of human livelihood. For instance, weather forecasting provides decision making support for autonomous vehicles to reduce traffic accidents and congestions, which completely depend on the sensing and predicting of external environmental factors such as rainfall, air visibility and so on. Accurate and timely weather prediction has always been the goal of meteorological scientists. However, the conventional theory-driven numerical weather prediction (NWP) methods face many challenges, such as incomplete understanding of physical mechanisms, difficulties in obtaining useful knowledge from the deluge of observation data, and the requirement of powerful computing resources. With the successful application of data-driven deep learning method in various fields, such as computer vision, speech recognition, and time series prediction, it has been proven that deep learning method can effectively mine the temporal and spatial features from the spatio-temporal data. Meteorological data is a typical big geospatial data. Deep learning-based weather prediction (DLWP) is expected to be a strong
Who reads Deep Learning-Based Weather Prediction: A Survey?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Xiaoli Ren; Xiaoyong Li; Kaijun Ren; Junqiang Song; Zichen Xu; Kefeng Deng; Xiang Wang
- Publisher
- Elsevier BV
- Published
- 2021
- Language
- EN
- Field
- Computer Science (Physical Sciences)