Nathaniel Troutman

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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(More)
  • Amy Mcgovern, Timothy Supinie, David John Gagne Ii, Nathaniel Troutman, Matthew Collier, Rodger A Brown +2 others
  • 2010
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(More)
Many real world domains are inherently spatiotemporal in nature. In this work, we introduce significant enhancements to two spatiotemporal relational learning methods, the spatiotemporal relational probability tree and the spatiotemporal relational random forest, that increase their ability to learn using spatiotemporal data. We enabled the models to(More)
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(More)
  • Nathaniel Troutman, Norman Oklahoma, Amy Mcgovern, F Dean, Andrew H Hougen, Kelvin Fagg +2 others
  • 2010
Acknowledgments First and foremost I'd like to thank my wife, Megan, and my family for encouraging me to follow my interests in computer science and artificial intelligence and to actually finish the process of obtaining a Masters degree.
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