Abstract: A method and an apparatus for learning an artificial neural network for data prediction. The method includes: obtaining first output data through a first artificial neural network for future data prediction based on an input time series data set; obtaining second output data through a second artificial neural network for past data reconstruction using the first output data of the first artificial neural network; calculating a cost function using the first output data of the first artificial neural network and the second output data of the second artificial neural network; and learning the first artificial neural network using the cost function.

Abstract: Provided is a mobile terminal including a display unit to which multiple images are output; a sensing unit that detects a touch gesture as being applied to a first image among the multiple images; and a controller that changes an output state of the first image based on the touch gesture. In a state where the output state of the first image is output, when at least one image is selected from among the multiple images, the controller performs control in such a way that at least one selected image overlaps the first image serving as a reference image, and sets the first image and at least one image that overlaps the first image serving as the reference image so that the first image and at least one image belong to a first group. Accordingly, the stored multiple images are quickly categorized on one screen without being moved to a different screen.