pattern recognition

OPTIMIZATION OF OBJECT DETECTION IN CLOSED SPACE USING MOBILE ROBOTIC SYSTEMS WITH OBSTACLE AVOIDANCE

Introducing neural network training process modification that uses combination of several datasets to optimize search of objects and obstacles using mobile robotic systems in a closed space. The study includes an analysis of papers and existing approaches aiming to solve the problem of object boundary detection and discovers the key features of several neural network architectures. During research, it was discovered that there is an insufficient amount of data about the effectiveness of using obstacle detection approaches by mobile robotics systems in a closed space.

Multi-criteria decision making based on novel distance measure in intuitionistic fuzzy environment

In comparison to fuzzy sets, intuitionistic fuzzy sets are much more efficient at representing and processing uncertainty.  Distance measures quantify how much the information conveyed by intuitionistic fuzzy sets differs from one another.  Researchers have suggested many distance measures to assess the difference between intuitionistic fuzzy sets, but several of them produce contradictory results in practice and violate the fundamental axioms of distance measure.

CONVERGENCE PROBLEM SCHEMES FOR CONSTRUCTING STRUCTURES OF LOGICAL AND ALGORITHMIC CLASSIFICATION TREES

The problem of convergence of the procedure for synthesizing classifier schemes in the methods of logical and algorithmic classification trees is considered. An upper estimate of the complexity of the algorithm tree scheme is proposed in the problem of approximating an array of real data with a set of generalized features with a fixed criterion for stopping the branching procedure at the stage of constructing a classification tree.