The present invention relates to a machine learning-based system for predicting a distribution and movement path of a source (a light source, electricity, magnetism, radiation) in a 3-dimensional space, and a method therefor and, more particularly, to a machine learning-based system for predicting a distribution and movement path of a source on a 3-dimensional space, and a method therefor, wherein source information and location information of the source according to time are obtained while moving the source on the 3-dimensional space and also a data set of response signals according to time is obtained by a plurality of detectors, an artificial neural network is machine-learned by inputting the source information and the location information of the source according to time to an output node of the artificial neural network and inputting the data set of the response signals according to time to an input node thereof, a multi-source distribution is predicted by repeatedly selecting and overlapping pieces of training data according to time of an arbitrary single source, and the movement path of the source is predicted by inputting the data set of the response signals according to time from the plurality of detectors to the machine-learned artificial neural network.
MACHINE LEARNING-BASED SYSTEM FOR PREDICTING DISTRIBUTION AND MOVEMENT PATH OF SOURCE IN 3-DIMENSIONAL SPACE, AND METHOD THEREFOR