Space Weather Physics: Dynamic Neural Network Studies of Solar Wind-Magnetosphere Coupling
This thesis presents studies of solar wind-magnetosphere coupling using dynamic neural networks in combination with statistically correlative analysis. The primary contribution of the thesis is dynamic neural network models that can be implemented for near real-time predictions of geomagnetic storms from the solar wind alone. With acceptable accuracy, the prediction time has been extended up to 5