articles
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№ 2(68)
29 april 2017 year
Rubric: Actor modeling Authors: Emelyanov A., Bulygina O. V., Dli M. I., Emelyanova N. |
Decision making by the aircrafts services of the international airport, which provides for
intensive traffic of aircraft and their ground handling, becomes a very topical issue. If earlier it
was believed that the intensity is provided only by the number of runways, nowadays a large
accumulation of aircraft on the airport platform-field creates equally complex difficulties in
comparison with aircraft take-offs and landings. Solving such problems with the use of «crisp
methods» of queuing theory gives little. This article deals with modern «fuzzy methods» based
on simulation modeling and fuzzy logic.
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№ 2(68)
29 april 2017 year
Rubric: Models and Methods Authors: Rezchikov A., Bogomolov A., Filimonyuk L., Ivaschenko V., Kushnikov V., Yandybaeva N. |
Actual today is the development of mathematical models for simulation experiments to ensure the
country’s transition to sustainable development. The main indicators of national security, according to
Presidential Decree № 683 «National Security Strategy of the Russian Federation» are: satisfaction of citizen
of degree of protection of their constitutional rights and freedoms, personal and property interests,
including from criminal encroachments; the share of modern weapons, military and special equipment
in the Russian Armed Forces; the life expectancy; gross domestic product per capita; inflation; the share
of expenditure in the gross domestic product for culture, as well as the development of science, technology
and education; the part of the territory of the Russian Federation, that do not meet environmental
standards. Developed a complex of mathematical models for modeling and the prognostication indicators
of Russia’s national security. Mathematical model developed based on system dynamics models,
allows formalizing the complex casual relationships between system variables. System dynamics model
consists of the following elements: the system levels (the simulated variables), which represent the accumulation
of (accumulation) in feedback circuits; streams conveying the content of one level to another;
making procedures that govern the rate of flow between the levels; information channels connecting procedures
decisions levels. To describe the model developed using the apparatus of ordinary differential
equations. As systemic levels presented the indicators of national security. To illustrate the casual relationships
between system-level mathematical model developed using the graph model. Regression models
are used to verify the adequacy of system dynamics models. An algorithm is proposed for determining
of indicators of national security for solves the system of nonlinear differential equations. Shows the
practical implementation of the mathematical support developed and compared predictive values of indicators
of national security. Performed modeling of chaotic phenomena in the Russian economy in 1994.
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№ 2(68)
29 april 2017 year
Rubric: Models and Methods Authors: Arutyunov A., Nikulina I., Zatonskaya O. |
Market volume forecasting is one of the most essential steps in new aircraft development determining
critical inputs for sales, manufacturing, finance, after sales support, etc. For aircraft industry
forecasting challenges are due to technical characteristics, long-lasting development process and life
cycles, that requires forecasting for 10 – 20 or more years. Authors’ experience proves the importance
of combined analytical and expert approach in aircraft market volume forecasting for both short and
long-term periods. Analytical method is demonstrated in the article. Aircraft market volume is equal to
the sum of fleet development forecast and removal from service forecast minus current fleet in terms of
the number of aircraft. Fleet development forecasting is executed using Singular Spectrum Analysis.
Removal from service forecasting is executed with use of Survivor Curve Analysis. Both Singular
Spectrum Analysis and Survivor Curve Analysis are shortly described in the article. Results of passenger
widebody airplane segment forecasting for 20 years is given as an example. To test the efficiency
of the proposed analytical method forecasting using historical data is executed which means shortening
the initial time series on 5, 10, 15 and 20 points and executing a forecast on the respective time
period. Test results demonstrate precise fit of the historical data and forecast for 5 and 10 years forecasting.
For 15 years forecasting is properly done in terms of numerical aspect but improper in terms
of qualitative aspect. To test validity of the forecasting for 20 years the results were compared with
Boeing Current Market Outlook 2015, the difference was less than 0.3%. Reckoning on the Boeing’s
data is due to the hypothesis of lack of the statistical data while forecasting for 20 years.
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Optimization problems have received attention in different research areas. This article provides an
overview of the methods of searching for the global minimum. The paper presents a new algorithm for
solving one-dimensional function optimization problem. The algorithm employs random variables and
events. The algorithm generates two types of elements: search and exploration. The elements of the
first type strive to explore the unexplored areas. The probability of failing into each interval depends
on the distance between the points. The elements of the second type examine the areas where the objective
function takes the best value. The probability of failing into each interval depends on the objective
function value. The ratio of searching elements depends on the task. If we need to find all local
minima, it is better to use elements of the search. To obtain a more accurate solution, the number
of exploration elements is increased. Solution to two examples described. Results of computational
experiments comparing the presented algorithm with other known algorithms are presented. The result
showed that the solution could be found for a smaller number of steps compared with the simple
random search algorithm.
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Business entities performance is inextricably linked with information resources sharing today. This
problem can be solved by information systems integration. Often IT is not company’s core function
and information system integration is carried out using IT-outsource. Architecture patterns choice and
information system development project management are keys in this case. This article suggests relevant
to modern conditions information systems integration architecture patterns. Information system
life cycle stages and information systems development project stages interrelation model taking in the
account information risks influence is suggested for effective information system development project
management. Decision support system architecture is suggested for information risks minimization
during information systems development project. Suggested results practical utilization is assumed
towards the development of business entities information system integration project management.
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The relevance of the study is due to the need to ensure the effective functioning of innovative regional
industrial clusters, including the innovation-active industrial enterprises and organizations of
innovation infrastructure. This article is based on a proposal for integration of information resources
of all participants in a complex innovation process with the use of innovation management decision
support in clusters of a specified type. A leading approach in the study is the controlling methodology
application, allowing to identify the main internal and external environment factors to select rational
tools of information management support in innovative regional industrial clusters.
The article presents the model of information exchange between integrated innovation process participants
in the innovation territorial industrial clusters in the implementation of controlling functions,
which are coordinated by the center of the controlling cluster. The model identified the main functional
areas of the controlling system, corresponding to six cycles of a complex innovation process, as well
as four levels of controlling information processes in the cluster: controlling content, controlling applications,
controlling processes, controlling of cluster complex information integration and its region
localization. As an example, such issue as the task of classification and selection of innovative proposals
(including open innovation) for their further use by the cluster enterprises based on four types innovative
filters was solved by the proposed controlling information flows system.
The article can be useful for creating regional information systems providing information support
of management processes in territorial innovation industrial clusters.
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