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Models and intellectual technologies used for analysis and process management under uncertainty

Author

Listed:
  • Vladislav SKALOZUB

    (Ukrainian State University of Science and Technologies, Dnipro, Ukraine)

  • Vadim HORIACHKIN

    (Ukrainian State University of Science and Technologies, Dnipro, Ukraine)

  • Ivan KLYMENKO

    (Ukrainian State University of Science and Technologies, Dnipro, Ukraine)

Abstract

Objectives: Modern production activity of railway transport of Ukraine (RTU) is characterized by high the level of complexity of processes and a wide range of conditions of uncertainty. The article is devoted to the tasks of development of unified automated intelligent analysis and control technologies indeterminate RTU processes in case of uncertainty. Methods / Approach: To achieve the goal a new model of the concept of formation of automated intellectual technologies of RTU is offered, implementation of which is based on a modular platform of unified analytical services designed for effective solution of certain typical tasks (diagnosis, classification, forecasting, management, etc.). The concept as a system includes stages of research of properties of processes, theoretical and methodological basis and methods of modeling and automated control, scenarios and intelligent acceptance procedures decisions in case of uncertainty. Results: As examples of application of the concept to the formation of unified technologies RTU presented intelligent services for diagnosing processes with several categories of uncertainty, as well as analysis and forecasting the parameters of anti-resistance processes. The analysis procedures developed in the article differ using the scheme of fuzzy control method Takagi-Sugeno adapted for diagnostic tasks with the uncertainty of different types (statistical, fuzzy, etc.), which is provided by the use integrated indicator – the reliability index, as well as the formal capabilities of the individual accounting for the importance of controlled variables of the process model together for all rules of diagnosis, and for each rule separately. By aggregating the levels of time series of non-deterministic RTU processes developed and researched correct mathematical models and algorithms designed for unified procedures classification and research of properties of anti-persistent processes of railway transport. Conclusions: In order to develop unified intelligent automated technologies RTU developed a concept analysis and management of non-deterministic RTU processes in case of uncertainty based on the platform analytical services. In work at formation of the specified services of the automated intellectual The technology has developed advanced diagnostic procedures that use Takagi-Sugeno-type models for several categories of uncertainty, as well as methods for classifying anti-persistence processes, algorithms interpolation of levels within aggregation ranges, analysis models and short-term forecasting processes designed to develop the theoretical basis and means of improving automated systems RTU.

Suggested Citation

  • Vladislav SKALOZUB & Vadim HORIACHKIN & Ivan KLYMENKO, 2022. "Models and intellectual technologies used for analysis and process management under uncertainty," Access Journal, Access Press Publishing House, vol. 3(2), pages 185-200, April.
  • Handle: RePEc:aip:access:v:3:y:2022:i:2:p:185-200
    DOI: 10.46656/access.2022.3.2(8)
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    More about this item

    Keywords

    railway transport; unified intellectual technologies; non-deterministic processes; uncertainty; diagnostics; anti-persistence processes; accuracy of classification;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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