Abstract
The article is devoted to the problem of modeling the speed of movement of timber trucks in various natural conditions of the Krasnoyarsk Territory. The results were obtained on the basis of multiple observations of the speed of timber trucks on various sections of forest roads. The results presented in the article are based on the selection and analysis of factors that can presumably have any effect on the speed of movement of timber trucks when hauling timber. The article presents the results of creating a multifactorial dependence for calculating the speed of timber transport. The analysis of the quality factor of each of the factors is carried out by the rank distribution of the obtained regularities and by compiling a rating of the conducted field experiments on the multivariate analysis of timber removal. The calculations and modeling were carried out in the CurveExpert-1.40 software environment and the Microsoft Office Excel software package in the RANK environment. Using the CurveExpert-1.40 software environment, the adequacy of the regularities of the rank distributions of the factors of timber removal from the forest area was assessed by the correlation coefficient. As a result, we obtained models of the total and private influence of factors from themselves (monar ratio) by ranks, which were placed before modeling for each factor in the direction of changing the level of their preference for factors from worse to better. When analyzing the quality factor of experiments, all analyzed factors received a correlation coefficient above 0,97, which corresponds to the level of adequacy of the «strongest factor relationship». This made it possible to add up the ranks of all 35 factors and, by the sum of the ranks, reveal the rating in the system of factors. The paper presents the mathematical dependences of rank distributions and graphs constructed from them. As a result of modeling, regression dependences were obtained and the quality factor of the values of the factors used by the authors in the course of production experiments was proved.
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