Abstract
During 2015—2020, wear and tear of the fleet of dustcarts of municipal enterprises of Vinnytsia decreased from 81 % to 63.8 %. Therefore, the determination of the regression dependence describing the dynamics of wear and tear of dustcarts in the Vinnytsia region to solve the problem of municipal solid waste management is an urgent scientific and technical task. The purpose of the study is to determine by means of a regression analysis of dependence, which describes the dynamics of wear and tear of dustcarts in the Vinnytsia region to solve the problem of municipal solid waste management. During the research, the method of regression analysis of the results of one-factor experiments and other paired dependencies was used with the selection of a more adequate type of function from the 16 most common options according to the criterion of the maximum correlation coefficient. The regression was carried out on the basis of linearizing transformations, which allow to reduce the non-linear dependence to a linear one. The coefficients of the regression equation were determined by the method of least squares using the developed computer program “RegAnaliz”, which is protected by a certificate of copyright registration for the work. An adequate regression dependence was obtained, which describes the dynamics of wear and tear of dustcarts in the Vinnytsia region. A graphical dependence has been constructed that describes the dynamics of wear and tear of dustcarts in the Vinnytsia region and allows to visually illustrate this dynamic, to show a sufficient convergence of theoretical and actual results. It was established that the wear and tear of dustcarts in the Vinnytsia region in 2015—2020 decreased according to a hyperbolic dependence. It is predicted that by 2030, the wear and tear of dustcarts in the Vinnytsia region will decrease to 61.9 % at the current rate of decline.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.