THE MULTI-FACTOR ESTIMATION OF THE RAILWAY TRANSPORTATION PROCESS INDICATORS TO FORECAST THE MOMENT THE OUTPUT INDICATORS ACHIEVED THE PREVIOUSLY DEFINED SPECIFIC VALUES

Receipt date: 
27.10.2018
Bibliographic description of the article: 

Yakhina A. S., Kuklina O. K. Mnogofaktornoye otsenivaniye pokazateley protsessa zheleznodorozhnykh perevozok s tsel'yu prognozirovaniya momenta dostizheniya rezul'tativnymi pokazatelyami zaraneye zadannykh konkretnykh znacheniy [The multifactor estimation of the railway transportation process indicators to forecast the moment the output indicators achieved the previously defined specific values]. Sovremennyye tekhnologii. Sistemnyy analiz. Modelirovaniye [Modern Technologies. System Analysis. Modeling], 2019, Vol. 61, No. 1, pp. 139–144. DOI: 10.26731/1813-9108.2019.1(61).139–144

Section: 
Year: 
2019
Journal number: 
УДК: 
519.6:311
DOI: 

10.26731/1813-9108.2019.1(61).139–144

Article File: 
Pages: 
139
144
Abstract: 

The multi-factor models of the second degree and parameter selection tools were used to create the model to estimate the moment the indicators of freight turnover and loading volume reached the previously defined specific values. The research was made according to statistical data of the Ulan-Bator railway. From ten factors, some of them turned out to be insignificant, and some of them had insignificant influence on output indicators. As a result, the following factors were used for research: for turnover – the average salary, mln. tugrics; exploitative fleet of the locomotives, loc/day; the average mileage of the locomotive, km/day; for freight loading, it is the average mileage of the locomotive, km/day; and the average salary, thous. tugrics. It is necessary to create a factor model (the forecast model for factors as a function of time) for each factor when using multi-factor models of the second degree in practice for the problem of forecasting output indicators. When the forecast values are defined that values can be used in multi-factor models and output indicators can be calculated and then using the goal seek tools the time period will be defined after which the turnover and loading volume will be more than previously defined specific values. All the classic forecasting tasks consist in predicting the values of model parameters or in predicting the values of the effective indicator for known values of parameters. This paper proposes a mechanism to determine the time when an effective indicator achieves the desired value.

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