Analysis of existing approaches to setting the intelligent management systems of transport undertakings
DOI:
https://doi.org/10.15587/1729-4061.2015.56693Keywords:
intelligent systems, dynamically variable objects, transport undertakingsAbstract
The problem of designing intelligent management systems (IMS) of dynamically variable objects (DO), operating under significant a priori uncertainty is considered. The analysis of existing approaches to developing DO IMS, methods, models and algorithms of their construction based on the integration of classical methods of management theory and artificial intelligence methods was presented. As examples of DO, rolling stock (TU) of the multi-mode enterprises is examined. The range of unresolved problems is identified, the purpose and objectives for the solution are formulated.
Currently, the problem of designing the automatic management systems of dynamically variable objects is characterized by the transition from the paradigm of adaptive management to the paradigm of intelligent management. This is caused by a continuous complication of management objects and conditions of their operation, the emergence of new classes of computing means (in particular, distributed computing systems), high-performance telecommunications channels, and a sharp increase in the reliability and efficiency requirements for management processes under significant a priori and a posteriori uncertainty. Accounting of these factors is possible only on the basis of transition from "hard" algorithms of parametric and structural adaptation to the anthropomorphic principle of management formation.
References
- Artsybashev, A. Y., Nikitin, R. Yu. (2014). Diagnosing drive vehicles based on neural networks. Acta Facultatis forestalis Zvolen, 56 (1), 201–208.
- Kostin, N. S. (2013). Mesto modul'nyh nejronnyh setej v klassifikacii iskusstvennyh nejronnyh setej. Intellektual'nyj potencial HHІ veka: stupeni poznanija, 19, 91–95.
- Sinchuk, O. N., Bojko, S. N. (2014). Nejronnye seti i upravlenie processom upravlenija jelektrosnabzheniem obektov ot kombinirovannyh jelektricheskih setej. Tehnichna elektrodinamika, 5, 53–55.
- Manzhula, V. G., Fedjashov, D. S. (2011). Nejronnye seti Kohonena i nechetkie nejronnye seti v intellektual'nom analize dannyh. Fundamental'nye issledovanija, 4, 108–114.
- Tarkov, M. S. (2013). Otobrazhenie parallel'nyh programm na mnogojadernyh komp'juterah s rekurrentnymi nejronnymi setjami. Prikladnaja diskretnaja matematika, 2 (20), 50–58.
- Kolbasin, V. A. (2011). Parallel processing of data flow by artificial neural networks on the cuda platform. Eastern-European Journal of Enterprise Technologies, 3 (3 (51)), 54–57. Available at: http://journals.uran.ua/eejet/article/view/1560/1458
- Gorbacheev, S. V., Syrjamkin, V. I. (2014). Nejro–nechetkie metody v intellektual'nyh sistemah obrabotki i analiza mnogomernoj informacii. Tomsk: Izd–vo Tomskogo un–ta, 441.
- Semenov, A. M. (2014). Intellektual'nye sistemy. Orenburg: OGU, 236.
- Vasil'ev, A. N., Tarhov, D. A. (2014). Nejrosetevye metody i algoritmy matematicheskogo modelirovanija. St. Peterburg: Izd–vo Politehn. un–ta, 581.
- Jeshbi, U. R. (2014). Vvedenie v kibernetiku. Moscow: URSS: LENAND, 432.
- Andrejchikov, A. V., Andrejchikova, O. N. (2014). Sistemnyj analiz i sintez strategicheskih reshenij v innovatike. Moscow: URSS, 304.
- Guljaev, V. A. (1993). Tehnicheskaja diagnostika upravljajushhih sistem. Kyiv: Naukova dumka, 208.
- Denisov, A. A., Kolesnikov, D. M. (1982). Teorija bol'shih sistem upravlenija. Leningrad: Jenergoizdat, 288.
- Komarcova, L. G., Maksimov, A. V. (2002). Pejrokomp'jutery. Moscow: MGTU im. Baumana, 320.
- Kuzovkov, P. T. (1976). Modal'noe upravlenie i nabljudajushhie ustrojstva. Moscow: Mashinostroenie, 184.
- Sadovskii, M. G. (Ed.) (2014). Nejroinformatika, ejo prilozhenija i analiz dannjah. Krasnojarsk: IVM SO RAN, 195.
- Molchanov, I. N. (1987). Mashinnye metody reshenija prikladnyh zadach. Algebra, priblizhenie funkcij. Kyiv: Naukova dumka, 288.
- Mashkina, I. V. (1989). Reguljator peremennoj struktury chastoty vrashhenija rotora gazoturbinnogo dvigatelja v sisteme upravlenija reaktivnym soplom. Ufa: UAI, 21.
- Melsa, D., Dzhons, S. (1981). Programmy v pomoshh' izuchajushhim teoriju linejnyh sistem upravlenija. Moscow: Mashinostroenie, 199.
- Neterson, D. (1984). Teorija setej Netri i modelirovanie sistem. Moscow: Mir, 264.
- Gregor, D., Toral, S., Ariza, T., Barrero, F., Gregor, R., Rodas, J., Arzamendia, M. (2015). A methodology for structured ontology construction applied to intelligent transportation systems. Computer Standards & Interfaces. doi: 10.1016/j.csi.2015.10.002
- Larue, G. S., Rakotonirainy, A., Haworth, N. L., Darvell, M. (2015). Assessing driver acceptance of Intelligent Transport Systems in the context of railway level crossings. Transportation Research. Part F: Traffic Psychology and Behaviour, 30, 1–13. doi: 10.1016/j.trf.2015.02.003
- Satunin, S., Babkin, E. (2014). A multi–agent approach to Intelligent Transportation Systems modeling with combinatorial auctions. Expert Systems with Applications, 41 (15), 6622–6633. doi: 10.1016/j.eswa.2014.05.015
- Demin, D. A. (2012). Synthesis of optimal temperature regulator of electroarc holding furnace bath. Scientific Bulletin of National Mining University, 6, 52–58.
- Mendes, J., Araújo, R., Sousa, P., Apóstolo, F., Alves, L. (2011). An architecture for adaptive fuzzy control in industrial environments. Computers in Industry, 62 (3), 364–373. doi: 10.1016/j.compind.2010.11.001
- Wai, R.-J., Chen, M.-W., Yao, J.-X. (2015). Observer–based adaptive fuzzy–neural–network control for hybrid maglev transportation system. Neurocomputing, 175, 10–24. doi: 10.1016/j.neucom.2015.10.006
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2015 Денис Юрійович Зубенко, Андрій Віталійович Коваленко, Олександр Миколайович Кузнєцов
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.