Handling the Problem of Unbalanced Data Sets in the Classification of Technical Equipment States

Questions of handling unbalanced data considered in this article. As models for classification, PNN and MLP are used. Problem of estimation of model performance in case of unbalanced training set is solved. Several methods (clustering approach and boosting approach) considered as useful to deal with the problem of input data

Combined system of precise positioning of pilotless helicopter-type aircraft in the landing area

On-board equipment, ground equipment, and special software have been developed and tested that makes it possible to determine with high accuracy the relative coordinates of a helicopter-type unmanned aerial vehicle relative to a quick deployment runway in the absence of signals from global navigation systems