Forecast Oriented Classification of Spatio-Temporal Extreme Events
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 2952-2953.
Abstract
In complex dynamic systems, accurate forecasting of extreme events, such as hurricanes, is a highly underdetermined, yet very important sustainability problem. While physics-based models deserve their own merits, they often provide unreliable predictions for variables highly related to extreme events. In this paper, we propose a new supervised machine learning problem, which we call a forecast oriented classification of spatiotemporal extreme events. We formulate three important real-world extreme event classification tasks, including seasonal forecasting of (a) tropical cyclones in Northern Hemisphere, (b) hurricanes and landfalling hurricanes in North Atlantic, and (c) North African rainfall. Corresponding predictor and predict and data sets are constructed. These data present unique characteristics and challenges that could potentially motivate future Artificial Intelligent and Data Mining research.
@inproceedings{ijcai2013p433,
title = {Forecast Oriented Classification of Spatio-Temporal Extreme Events},
author = {Chen, Zhengzhang and Xie, Yusheng and Cheng, Yu and Zhang, Kunpeng and Agrawal, Ankit and Liao, Wei-keng and Samatova, Nagiza F. and Choudhary, Alok N.},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {2952--2953},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/433},
}
TY - CPAPER TI - Forecast Oriented Classification of Spatio-Temporal Extreme Events AU - Chen, Zhengzhang AU - Xie, Yusheng AU - Cheng, Yu AU - Zhang, Kunpeng AU - Agrawal, Ankit AU - Liao, Wei-keng AU - Samatova, Nagiza F. AU - Choudhary, Alok N. T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 2952 EP - 2953 UR - https://ijcai.org/proceedings/2013/433 ER -Copied
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