Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning
نویسندگان
چکیده
منابع مشابه
Understanding Severe Weather Processes through Spatiotemporal Relational Random Forests
Major severe weather events can cause a significant loss of life and property. We seek to revolutionize our understanding of and ability to predict such events through the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining such data requires a model capable of representing and reasoning about complex spatiotemporal dynamics, including temporally and...
متن کاملSevere Weather Processes through Spatiotemporal Relational Random Forests
Major severe weather events can cause a significant loss of life and property. We seek to revolutionize our understanding of and ability to predict such events through the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining such data requires a model capable of representing and reasoning about complex spatiotemporal dynamics, including temporally and...
متن کاملUsing spatiotemporal relational random forests to improve our understanding of severe weather processes
Major severe weather events can cause a significant loss of life and property. We seek to revolutionize our understanding of and our ability to predict such events through the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining such data requires a model capable of representing and reasoning about complex spatiotemporal dynamics, including temporally...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2013
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-013-5343-x