Neural Decision Tree: A New Tool for Building Forecast Models for Plasmasphere Dynamics

The Neural Decision Tree (NDT) is a hybrid supervised machine-learning algorithm that combines the self-limiting property of decision tree (CART) with artificial neural network (ANN). We demonstrate use NDT for regression problem building prediction model plasmasphere electron density solar and geomagnetic measurements as inputs. Our work replicates by Zhelavskaya et al. reported in their 2017 article (I. S. al., 2017) to show makes available sophisticated layout predictive model, thus taking advantage deep-learning potential network. also ability automatically select an appropriate layout, well as, effective initialization, allows research scientists space weather focus more attention on physically statistically relevant aspects using techniques. In fact, our example highlights fact basic assumptions standard supervise problems are often unsatisfied real-world applications. Greater these fundamental issues may create significantly different solutions forecast problems.