Neural classification for interval information

Abstract

The subject of the presented research is to determine the complete neural procedure for classifying inaccurate information, as given in the form of an interval vector. For such a formulated task, a basic functionality Probabilistic Neural Network was extended upon the interval type of information. As a consequence, a new type of neural network has been proposed. The presented methodology was positively verified using random and benchmark data sets. In addition, a comparative analysis of existing algorithms with similar conditions was made.