Mathematical models and soil fertility management software

Abstract

The article presents the results of studies on parametric approximation in spaces R2 (functions of one variable), R3 (functions of two variables) and Rn(n>3) (functions of three or more variables). Various classes of functions satisfying a priori conditions were studied: f(0, 0, 0)=0, , ci = cont. Working algorithms and C/C++ software functioning in Microsoft Visual Studio 2019 system in Microsoft Windows 10 environment were developed. The main studies of the authors were aimed at developing effective computational algorithms for constructing approximating functions of two variables from various given classes of three-dimensional data samples (three-dimensional interconnected time series). The article provides a detailed description of the problem statement, introduces classes of approximating functions, provides algorithms for estimating the parameters of approximating functions and a description of the software. The estimation algorithm considered in the article is constructed according to the scheme of the coordinate descent method with optimization of the step length (Gauss-Seidel method).