Abstract

In the period of 2014 – 2020 the growth of the dust-carts fleet in Ukraine was 14 %. Determination of the regression dependence, describing the dynamics of the number of dust-carts growth in Ukraine is an important scientific-technical problem. Objective of the study is determination of the regression dependence, describing the dynamics of the dust-carts growth in Ukraine and can be used for the prediction of the amount of the dust-carts. In the process of the study the method of regression analysis of the results of single-factor experiments and other paired dependences with the selection of the rational type of function from the sixteen most widely used variants by the criterion of the maximum value of the correlation coefficient has been used. Regression was performed on the base of the linearizing transformations, which enable to reduce the non-linear dependence to linear one. Determination of the coefficients of the regression equations was carried out, applying the method of the least squares by means of the developed computer program "RegAnaliz", protected by the Certificate of the State registration of the rights to the copyright object. Adequate regression arch-tangential dependence, describing the dynamics of dust-carts quantity growth in Ukraine has been obtained, it can be used for the prediction of the number of dust-carts. Graphic dependence, describing the dynamics of the dust-carts number increase in Ukraine, allows to illustrate this dynamics and show the sufficient convergence of the theoretical results with actual data has been constructed. Using the obtained dependence, it is predicted that the number of the dust-carts in Ukraine, taking into account the existing rate of growth will reach 3873 units in 2030.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

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.