Typhoon and Extreme Precipitation and Wind Wave Prediction by Big Data Technology
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".
Deadline for manuscript submissions: closed (4 December 2020) | Viewed by 6289
Special Issue Editor
Interests: weather forecasting; remote sensing applications; tropical cyclones; ocean informatics, machine learning; deep learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Guest Editor is inviting submissions for a Special Issue of Atmosphere on the subject of “Typhoon and Extreme Precipitation and Wind Wave Prediction by Big Data Technology”.
Typhoons (tropical cyclones) as well as extreme events are the most destructive types of natural disasters. These severe typhoons and extreme events drastically affect the land surface and coastal areas through powerful winds and torrential rain. Nowadays, forecasting the behavior of complex typhoon systems has been a broad application domain for Big Data technology, such as machine learning, deep learning, neural networks, and Hadoop parallel computing. Particularly, predictions regarding rainfall, wind, and wind-wave caused by typhoons provide critical information that can be used for flood control and advanced disaster prevention preparations.
This Special Issue focuses on applications of Big Data techniques and machine learning methodologies in the field of typhoon precipitation, wind, and wind-wave predictions. Topics of interest for publication include, but are not limited to:
- Predictions in rainfall, wind, and wind-wave caused by typhoons and extreme events
- Big Data technical developments in typhoon-induced problems
- Machine learning methodologies in typhoon-induced problems
- Deep learning methodologies in typhoon-induced problems
- Neural network-based methodologies in typhoon-induced problems
- Application of Hadoop framework and parallel computing
- Case studies and analyses as well as assessments
Dr. Chih-Chiang Wei
Guest Editor
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Precipitation prediction
- Wind prediction
- Wind-wave prediction
- Typhoon, tropical cyclone, and extreme event
- Big data technology
- Hadoop parallel computing
- Machine learning
- Deep learning and deep neural networks
- CNN, RNN, LSTM networks
- Other advanced networks
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