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Abstract

In this article we construct a finite-difference scheme for the three-dimensional equations of the atmospheric boundary layer. The solvability of the mathematical model is proved and quality properties of the solutions are studied. A priori estimates are derived for the solution of the differential equations. The mathematical questions of the difference schemes for the equations of the atmospheric boundary layer are studied. Nonlinear terms are approximated such that the integral term of the identity vanishes when it is scalar multiplied. This property of the difference scheme is formulated as a lemma. Main a priori estimates for the solution of the difference problem are derived. Approximation properties are investigated and the theorem of convergence of the difference solution to the solution of the differential problem is proved.
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Authors and Affiliations

Almas N. Temirbekov
Urmashev Baydaulet A.
Konrad Gromaszek
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Abstract

The article deals with the features and characteristics of intelligent systems for modelling business processes. Their classification was made and criteria for comparison were developed. According to the comparative analysis of existing expert systems for intelligent analysis, a reasonable choice of system for modelling business processes of a particular enterprise has been carried out. In general, it was found that the introduction of intelligent systems for modelling business processes of the enterprise and forecasting its activities for future allows management of the company to obtain relevant and necessary information for the adoption of effective management decisions and the development of a strategic plan.
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Bibliography

[1] B. V. Kuzmenko, and O. A. Chaikovska, “The systems of artificial intelligence,” Kyiv, Alterpres, 2006.
[2] H. F. Ivanchenko,“The systems of artificial intelligence,” Kyiv, KNEU, 2011.
[3] D. F. Liuher, “The artificial intelligence: strategies and methods of solving difficult issues,” Moscow, Vyliams (in Russian), 2003, pp. 866.
[4] A. A. Emelianov, E. A. Vlasova, and R. V. Duma, “Simulation modeling of economic systems,” Moscow, Finansy i statistika (in Russian), 2002.
[5] D. Waterman, “Guide to expert systems,” Moscow, Myr, 1989.
[6] A. A. Barsehian, M. S. Kupryianov, V. V. Stepanenko, and Y. Y. Kholod, “Methods and models of data analysis: OLAP and Data Mining,” St-Petersburg, BKhV, 2004.
[7] V. Mashkov and A. Smolarz and V. Lytvynenko, “The problem of system fault-tolerance,” Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska (IAPGOŚ), 4(4), pp. 41-44, 2014.
[8] Z. Omiotek and W. Wójcik, “The use of Hellwig's method for dimension reduction in feature space of thyroid ultrasound images,” Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 4(3), pp. 14-17, 2014.
[9] P. V. Poliakov, and S. A. Korobov, “Software tools for developing business plans: Project Expert system,” Volhohrad, vol. HU, pp. 48, 2004.
[10] H. S. Prokudin, M. T. Dekhtiaru, “Simulation modeling in informational systems,” Kyiv: NTU., no. 9, pp. 181–189, 2004.
[11] A. P. Rotshtein, and H. B. Rakytyanska, “Diagnosis problem solving using fuzzy relations,” IEEE Transactions on Fuzzy Systems, vol. 16, no. 3, pp. 664-675, 2008.
[12] S. I. Vyatkin, A. N. Romanyuk, and Z. Y. Gotra, “Offsetting, relations, and blending with perturbation functions,” Proc. of SPIE 10445, 2017.
[13] L. I. Timchenko, S. V. Pavlov, N. I. Kokryatskaya, et al. “Bio-inspired approach to multistage image processing,” Proc. of SPIE 10445, 2017.
[14] M. F. Kirichenko, Yu. V. Krak, A. A. Polishchuk, “Pseudo inverse and projective matrices in problems of synthesis of functional transformers,” Kibernetika i Sistemnyj Analiz, vol. 40, no. 3, pp. 116-129, 2004.
[15] K. G. Selivanova, O. G. Avrunin and S. M. Zlepko, “Quality improvement of diagnosis of the electromyography data based on statistical characteristics of the measured signals,” Proc. of SPIE 10031, 2016.
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Authors and Affiliations

Svetlana A. Yaremko
1
Elena M. Kuzmina
1
Nataliia B. Savina
2
Konrad Gromaszek
3
Bakhyt Yeraliyeva
4
Gauhar Borankulova
4

  1. Vinnytsia Institute of Trade and Economics of Kyiv National University of Trade and Economics, Ukraine
  2. National University of Water and Environmental Engineering, Rivne, Ukraine
  3. Lublin University of Technology, Lublin, Poland
  4. Taraz State University after M.Kh.Dulaty, Taraz, Kazakhstan
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Abstract

The possibility and expediency of estimation of risk factors based on fundamental positions of information and entropy are grounded. In accordance with the principle of addiction, the possibility of using the H-criterion as an indicator of business uncertainty is shown. The algorithm of risk estimation of these investments is offered.
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Bibliography

[1] D. A. Endovutskiy, “Complex analysis and control of investment activity: methodology and practice,” in Finance and statistics, 2001, pp. 4–400.
[2] V. M. Anshun, “Investment analysis: Study practice allowance,” in Delo, 2000, pp. 1–280.
[3] E. Nickbaht, and A. Gropelli, “Finance 17th ed.,” in Barrons Educational Series, New York, 2018, pp. 1–640.
[4] A. I. Zagorodniy, “Financial Vocabulary,” in Znannia, 2000, pp. 21–87.
[5] V. V. Vitlinskiy, and S. I. Nakonechnyj, “Risk in management,” in LLC Borysphen-M, 1996, pp. 15–336.
[6] A. Vorontsovskyj, “Analysis and basement of investment decisions on the stock market,” in Problems of theory and practice of management, 1996, pp. 104–109.
[7] A. S. Grinberg, R. M. Kachalov, and V. N. Shander, “Dual management on the base of risk theory in lifelong cycle man-machine system,” in Computer science-89, Minsk, 1989, pp. 891–896.
[8] L. O. Bakaev, “Quantitative methods at investment management,” in KNEU, 2000, pp. 131–151.
[9] A. P. Nesenyuk, “Undetermined dimensions in management with incomplete information,” Moscow: Mir, 1978, pp. 55–64.
[10] C. Shannon, “Works on theory information and cybernetics,” Moscow: Mir, 1963, pp. 54-223.
[11] C. E. Shannon, “Mathematical Theory of Communication,” The Bell System Technical Journal, vol. 27, pp. 379–423 and 623-656, 1948.
[12] A. S. Kovalenko, S. V. Tymchyk, S. V. Kostyshyn, S. M. Zlepkoand W. Wójcik, A. Kalizhanova, A. Burlibay and A. Kozbekova., “Concept of information technology of monitoring and decision-making support,” Proc. of SPIE 10445, pp. 95–101, 2017.
[13] A. P. Rotshtein, M. Posner, and H. B. Rakytyanska, “Cause and effect analysis by fuzzy relational equations and a genetic algorithm,” Reliability Engineering and System Safety, vol. 91, no. 9, pp. 1095–1101, 2006.
[14] V. Mashkov, A. Smolarz and V. Lytvynenko, “The problem of system fault-tolerance,” Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska (IAPGOŚ), vol. 4, no. 4, pp. 41–44, 2014.
[15] L. I. Timchenko, “A multistage parallel-hierarchic network as a model of a neuronlike computation scheme,” Cybernetics and Systems Analysis, vol. 36, no. 2, pp. 251–267, 2000.

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Authors and Affiliations

Nataliia B. Savina
1
Nina V. Slyusarenko
2
Maryna S. Yakobchuk
1
Konrad Gromaszek
3
Saule Smailova
4
Kuanysh Muslimov
5

  1. National University of Water and Environmental Engineering, Rivne, Ukraine
  2. Kherson State University, Ukraine
  3. Lublin University of Technology, Lublin, Poland
  4. East Kazakhstan State Technical University named after D.Serikbayev, Ust-Kamenogorsk, Kazakhstan
  5. Kazakh National Research Technical University named after K.I.Satpayev, Almaty, Kazakhstan
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Abstract

The process of designing and creating an integrated distributed information system for storing digitized works of scientists of research institutes of the Almaty academic city is analyzed. The requirements for the storage of digital objects are defined; a comparative analysis of the open source software used for these purposes is carried out. The system fully provides the necessary computing resources for ongoing research and educational processes, simplifying the prospect of its further development, and allows to build an advanced IT infrastructure for managing intellectual capital, an electronic library that is intended to store all books and scientific works of the Kazakhstan Engineering Technological University and research institutes of the Almaty academic city.

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Authors and Affiliations

Nurlan M. Temirbekov
Tahir M. Takabayev
Dossan R. Baigereyev
Waldemar Wójcik
Konrad Gromaszek
Almas N. Temirbekov
Bakytzhan B. Omirzhanova

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