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Analysis of Indicators of the State of Regional Freight Traffic by Method of Fuzzy Linear Regression

机译:模糊线性回归方法分析区域货运状态的规定

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In this paper on the basis of statistical data 1996-2017 an analysis was made of the dependence of the volume of goods transported by road in the Rostov region on the density of public roads with hard surface, gross regional product per capita and tariff indices for freight traffic. When constructing regression equations on the basis of economic data, there is often an uncertainty that is associated with incomplete and vague information about the process being studied. In this reason, a fuzzy linear regression method is proposed for the analysis of this dependence. The linear regression coefficients are fuzzy symmetric triangular numbers. To find them, the corresponding optimization problem is solved. Two models were constructed, corresponding to the degrees of the fitting of the fuzzy linear model h = 0.4 and h = 0.5. The most adequate of the constructed fuzzy models is the model corresponding to the degree of the fitting of the fuzzy linear model h = 0.4, which is confirmed by the analysis of the control sample. At h = 0.5, the fuzziness coefficient increases sharply and the application of the model has no practical value. According to the results of the analysis, it was found that the index of tariffs for freight transportation has a decisive influence on the volume of cargo transportation.
机译:本文在统计数据的基础上,1996 - 2017年,分析了罗斯托夫地区路上路上的货物数量的依赖性,对具有硬表面的公共道路密度,人均毛额区域产品和关税指数货运。在基于经济数据的基础上构建回归方程时,通常存在与关于所研究过程的不完整和模糊信息相关的不确定性。因此,提出了一种用于分析这种依赖的模糊线性回归方法。线性回归系数是模糊对称三角形的数字。要找到它们,解决了相应的优化问题。构造了两种模型,对应于模糊线性模型H = 0.4和H = 0.5的拟合度。构造的模糊模型最适合的是对应于模糊线性模型H = 0.4的拟合程度的模型,通过对照样品的分析来确认。在H = 0.5,模糊系数急剧增加,模型的应用没有实用的价值。根据分析结果,发现货运的关税指数对货物运输量具有决定性影响。

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