Andrey Kostogryzov

Russian Academy of Sciences Russia

Andrey Kostogryzov is the Chief Researcher at the Computer Science and Control Federal Research Center of the Russian Academy of Sciences, Moscow. He obtained his doctorate of engineering in 1994 and was appointed a professor in 1999. He is deputy chairman of the Committee on Business Safety and chairman of the Information Technologies Subcommittee of the Russian Federation Chamber of Commerce and Industry. He is also chairman of the Special Expert Council of the Higher Attestation Commission, and a Certified Expert of the Russian Academy of Sciences, the Ministry of Education, and Gazprom. Dr. Kostogryzov was named an Honored Science Worker of the Russian Federation and received a Laureate of the Russian Government Award in the field of science and engineering in 2015. He is the author of more than 100 probabilistic models and more than 200 scientific works, including 21 books.

2books edited

3chapters authored

Latest work with IntechOpen by Andrey Kostogryzov

Probabilistic and combinatorial techniques are often used for solving advanced problems. This book describes different probabilistic modeling methods and their applications in various areas, such as artificial intelligence, offshore platforms, social networks, and others. It aims to educate how modern probabilistic and combinatorial models may be created to formalize uncertainties; to train how new probabilistic models can be generated for the systems of complex structures; to describe the correct use of the presented models for rational control in systems creation and operation; and to demonstrate analytical possibilities and practical effects for solving different system problems on each life cycle stage.

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Probability, Combinatorics and Control

Edited by Andrey Kostogryzov

Books edited

Probabilistic Modeling in System Engineering

Edited by Andrey Kostogryzov

Chapters authored

Some Applicable Methods to Analyze and Optimize System Processes in Quality Management

By Andrey Kostogryzov, George Nistratov and Andrey Nistratov

Part of the book: Total Quality Management and Six Sigma

Probabilistic Methods for Cognitive Solving of Some Problems in Artificial Intelligence Systems

By Andrey Kostogryzov and Victor Korolev

As a result of the analysis of dispatcher intelligence centers and aerial, land, underground, underwater, universal, and functionally focused artificial intelligence robotics systems, the problems of rational control, due to be performed under specific conditions of uncertainties, are chosen for probabilistic study. The choice covers the problems of planning the possibilities of functions performance on the base of monitored information about events and conditions and the problem of robot route optimization under limitations on risk of “failure” in conditions of uncertainties. These problems are resolved with a use of the proposed probabilistic approach. The proposed methods are based on selected probabilistic models (for “black box” and complex systems), which are implemented effectively in wide application areas. The cognitive solving of problems consists in improvements, accumulation, analysis, and use of appearing knowledge. The described analytical solutions are demonstrated by practical examples.

Part of the book: Probability, Combinatorics and Control

Probabilistic Predictive Modelling for Complex System Risk Assessments

By Andrey Kostogryzov, Nikolay Makhutov, Andrey Nistratov and Georgy Reznikov

The risks assessment is described by the action of estimating the probability distribution functions of possible successes or failures of a system during a given prediction period. Typical probabilistic predictive models and methods for solving risks prediction problems are described, and their classification is given. Priority development directions for risks prediction in standard system processes and their implementation procedures are proposed. The reported examples demonstrate the effects and interpretation of the predictive results obtained. Notes: 1. System is a combination of interacting elements organized to achieve one or more stated purposes (according to ISO/IEC/IEEE 15288 “Systems and software engineering—System life cycle processes”). 2. Risk is defined as the effect of uncertainty on objectives considering consequences. An effect is a deviation from the expected — positive and/or negative (according to ISO Guide 73).

Part of the book: Time Series Analysis

Andrey Kostogryzov

Latest work with IntechOpen by Andrey Kostogryzov

Probability, Combinatorics and Control

Books edited

Probabilistic Modeling in System Engineering

Chapters authored

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