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Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan Mar 2017

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …


Automated Generation Of Simulink Models For Enumeration Hybrid Automata, David Aaron Heise Aug 2013

Automated Generation Of Simulink Models For Enumeration Hybrid Automata, David Aaron Heise

Masters Theses

An enumeration hybrid automaton has been shown in principle to be ready for automated transformation into a Simulink implementation. This paper describes a strategy for and a demonstration of automated construction. This is accomplished by designing a data model which represents EHA data and providing a mapping from EHA data points to Simulink blocks.