Authors
Luzgin A.
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Degree
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PhD in Technique, Irkutsk State University |
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E-mail
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alexln@mail.ru |
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Location
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Irkutsk |
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Articles
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Test of the accuracy of the interval prediction based on confidence estimates of probabilities
The feature of forecasting in the process of management decision-making is the lack of constant
need to know an actual future value of the indicator. Most often, it is enough to know: will the future
value of the indicator exceed a predetermined value or not? The predetermined value divides the range
of possible future indicator values into two intervals. Since, in this case, we define the range in which
will be the future value of the indicator we call this method «interval forecasting».
The article proposes algorithmic and software of interval forecasting of dynamic indicators based on
an adaptive probabilistic statistical cluster model, where instead of the unknown probabilities are taken
account their point and interval estimates for the selected confidence probability. Authors show that
such a combined approach leads to improve interval forecasting accuracy and, as a result, improves the
quality of decision-making. The consequence of the combined approach is the increase of the number
of cases when the interval forecasting is not carried out. This is due to the fact, that some of point estimates
of probabilities are statistically indistinguishable. The number of these cases depends on statistical
characteristics, volume retrospective values of dynamic indicators and parameter values of the cluster
model. All the results in the article were obtained with the use of open-source programming language
«R», based on which was created a special software package for the end user. Improving the accuracy
of the interval forecasting is aimed at improving the efficiency of management decision-making, so the
software package can be used as a tool for the preparation of information for decision support system.
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Forecasting of base indicators of transportation process based on a scenario approach
A technology of base indicators complex forecasting of transportation process of railway transport
based on statistical and expert information using scenario approach have been developed. The cargo
turnover and cargo transportation volume have been selected as base indicators. Complex forecasting
based on four individual values with different weights: а) the value, which has been obtained by the
first-order model; b) the value, which has been obtained by the first-order model; c) the value, which
was obtained by the factor model; e) the point expert estimate of qualified specialists group. Developed
algorithms and software using statistical and expert information of Ulan-Bator Railway in relation to
the loading of goods have been approbated. It shows the good practical accuracy of complex forecasting
based on the scenario approach.
Read more...
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