Structural-parametric optimization of the experimental data decomposition into approximated fragments

Abstract

Abstract. In the process of modeling non-linear objects are often used piecewise approximation, spline methods or other methods based on their experimental data fragmentation. To effectively use fragmentation, it is necessary to develop and examine all the described stages of the approach. In this paper, a new approach to the selection of the structure of the decomposition of matrix data has been developed and proposed. It is based on the method of the ant colony, specially adapted for solving similar problems. Along with the characteristic properties of ant algorithms, special elements of interaction between agents of different colonies were introduced into this modification, for the efficient operation of the algorithm. The approach is considered as a tool for implementing the initial stage of any methods using data fragmentation. In the process of work, a software tool was designed and implemented in C #. The main data structures used in the software are described. Adjustment of the tuning parameters and the graphic output interface of the work process are implemented in the software tool. The graphical output was implemented by built-in tools. Test cases in detail describe the stages of data fragmentation under different initial parameters.