Mathematical models and methods of riks assessment in ecologically hazardous industries

Mikhalevich, V. S.; Knopov, P. S.; Golodnikov, A. N.

doi:10.1007/bf02366429

Cited by 11 publications

(3 citation statements)

References 4 publications

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“…3, on the interval I 1 = [04.12.20, 05.12.20], containing 31 observations, there are no more than one switching point at which NCC can vary (decrease or increase). Adding one switching point, where velocity probably varies, we obtain k = 2 in the estimation problem (10), (11). Its solution is estimates of switching points: $ t 1 4 = and $ t 2 19…”

Section: Constructing the Switching Regression On The Interval Imentioning

confidence: 99%

“…3, we suppose k = 2. The solution of the estimation problem (10), (11) where the notation in brackets have the same sense as in (18). According to (22), all the angular coefficients, except for $ a 13 , are highly significant, at the point $ t 1 sharp decrease has begun, followed by slow decrease at $ t 2 .…”

Section: Constructing the Switching Regression On The Interval Imentioning

confidence: 99%

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Statistical Analysis of the Dynamics of Coronavirus Cases using Stepwise Switching Regression

Knopov

Korkhin

2020

Cybern Syst Anal

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Section: Constructing the Switching Regression On The Interval Imentioning

confidence: 99%

Section: Constructing the Switching Regression On The Interval Imentioning

confidence: 99%

Statistical Analysis of the Dynamics of Coronavirus Cases using Stepwise Switching Regression

Knopov

Korkhin

2020

Cybern Syst Anal

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“…Uncertainty was and remains an inseparable feature of decision making. Stochastic programming methods and ideas can be fruitfully applied for risk management in economics and business [118,119]. Various authors are actively studying optimization methods (including stochastic quasigradient methods) for stochastic dynamic systems with discrete events.…”

Section: Here S(c X) ~ II (C X) C P(c X) C Xmentioning

confidence: 99%

Some directions and results of research in mathematical programming and system analysis

Сергиенко¹

1995

Cybern Syst Anal

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This article reviews the research in informatics, optimization theory, and system analysis associated with the scientific interests of our well-known scientist and mathematician, V. S. Mikhalevich, and his closest students and followers. We should qualify at the outset that the article does not review the full body of work of Mikhalevich, and certainly not of all his students: their work is much too extensive and much too multifaceted for one survey article. Moreover, in optimization theory, for instance, the Kiev mathematical school includes directions represented by other widely known scientists, and again these are not treated in the present article. I have decided to focus only on the studies and the directions of research to which V. S. Mikhalevich attached particular significance, which to a certain extent characterize his scientific creativity, and which are widely acknowledged among experts in our country and abroad.The active development of research in mathematical programming and system analysis at the National Academy of Sciences of Ukraine began in the late 1950s and early 1960s, when the Computational Center of the Academy of Sciences of the Ukrainian SSR and a number of other scientific organizations in the country focused on the creation of new computers and computer software. At that time, Academician V. M. Glushkov organized in Kiev a number of scientific seminars, which served as a starting point for studies in optimization theory, modeling of production processes, and computer-aided design of complex objects. Glushkov was apparently among the first cyberneticists who called attention to the need for the development of methods of system analysis, whose application in conjunction with modern computers to the study of complex processes in economics, medicine, engineering, and military science might achieve the desired goals. At that time, Mikhalevich himself, as well as his students and followers, were beginning their systematic work in this field. Their work was typically motivated by practical needs, and therefore immediately found wide applications for the solution of real-life problems.The studies reviewed in this article can be classified into three main groups: a) development and application of numerical optimization methods; b) informatization of society and issues of economic cybernetics; c) development of multiprocessor computers and computer software.

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Mathematical Methods of Adaptation of Crop Production to Climate Change

Golodnikov,

Knopov,

Pepelyaev

et al. 2024

Studies in Systems, Decision and Control

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Mathematical models and methods of riks assessment in ecologically hazardous industries

Cited by 11 publications

References 4 publications

Statistical Analysis of the Dynamics of Coronavirus Cases using Stepwise Switching Regression

Statistical Analysis of the Dynamics of Coronavirus Cases using Stepwise Switching Regression

Some directions and results of research in mathematical programming and system analysis

Mathematical Methods of Adaptation of Crop Production to Climate Change

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