About accuracy of risks prediction and importance of increasing adequacy of used probabilistic models

• Autorzy: Kostogryzov A. , Nistratov A. , Zubarev I. , Stepanov P. , Grigoriev L.
• Języki publikacji: EN

Abstrakty

EN

The work purpose is the quantitative proof of importance and necessity of increasing adequacy of probabilistic models, described by probability distribution functions (PDF) of time between losses of system integrity. For purpose achievement the analysis of probabilistic metrics of risks and the elementary forms to establish an admissible risks is carried out, some ways of increasing an adequacy of probabilistic models for complex structures are described. Possibilities of extracting the latent knowledge from an adequate PDF are shown. Practical value of the researches are the revealed possibilities for a substantiation of more effective system decisions at the expense of increasing accuracy of risks prediction. Effects are demonstrated by examples.

Słowa kluczowe

EN

model; optimization; probability; quality; resources; risk; system; technology

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2015
• Tom: Vol. 6, No. 2
• Strony: 71--80
• Opis fizyczny: Bibliogr. 10 poz., wykr.

Twórcy

autor

Kostogryzov A.

• Research Institute of Applied Mathematics and Certification, Moscow, Russia

autor

Nistratov A.

• Research Institute of Applied Mathematics and Certification, Moscow, Russia

autor

Zubarev I.

• Research Institute of Applied Mathematics and Certification, Moscow, Russia

autor

Stepanov P.

• Institute of Informatics Problems of the Russian Academy of Sciences, Moscow, Russia

autor

Grigoriev L.

• The Gubkin Russian State University of Oil and Gas, Moscow, Russia

Bibliografia

• [1] Kolowrocki, K. & Soszynska-Budny, J. (2011). Reliability and Safety of Complex Technical Systems and Processes. DOI:10.1007/978-085729-694-8, Springer-Verlag London Limited, 405.
• [2] Kostogryzov, A., Grigoriev, L., Nistratov, G., Nistratov, A. & Krylov, V. (2013). Prediction and Optimization of System Quality and Risks on the Base of Modelling Processes. American Journal of Operations Research, Special Issue, 3, 1A, 217-244. Available from: http://www.scirp.org/ journal/ajor/
• [3] Kostogryzov, A., Nistratov, A. & Nistratov, G. (2012). Applicable Technologies to Forecast, Analyze and Optimize Reliability and Risks for Complex Systems. Proceedings of the 6st International Summer Safety and Reliability Seminar, Poland, 3, 1, 1-14.
• [4] Kostogryzov, A. & Nistratov, G. (2004). Standardization, mathematical modelling, rational management and certification in the field of system and software engineering. Moscow, Armament. Policy. Conversion, 395 (in Russian)
• [5] Kostogryzov, A. I. & Nistratov, G. A. (2005). 100 Mathematical Models of System Processes According International Standards Requirements. Transaction of the XXV International Seminar on Stability Problems for the Stochastic Models. Maiority, Italy, University of Solerno, 196-201.
• [6] Kostogryzov, A., Nistratov, G. & Nistratov, A. (2012). Some Applicable Methods to Analyze and Optimize System Processes in Quality Management. Total Quality Management and Six Sigma, InTech, 127-196, 2012. Available from: www.intechopen.com/books/total-qualitymanagement-and-six-sigma/some-applicablemethods-to-analyze-and-optimize-systemprocesses-in-quality-management
• [7] Kostogryzov, A., Nistratov, G. & Nistratov, A. (2013). The Innovative Probability Models and Software Technologies of Risks Prediction for Systems Operating in Various Fields. International Journal of Engineering and Innovative Technology (IJEIT), 3, 3, 146-155. www.ijeit.com/archive.php
• [8] Kostogryzov, A.I. & Stepanov, P.V. (2008). Innovative management of quality and risks in systems life cycle, Moscow, Armament. Policy. Conversion, 404 (in Russian)
• [9] Nistratov, A. (2013). The technique of prediction of technogenic risks and its implementation by the use of Internet technology. The dissertation on a scientific degree PhD. Scientific supervisor – Stepanov P. V., Institute of Informatics Problems of the Russian Academy of Sciences, Moscow, Russia.
• [10] Zio, E. (2006). An Introduction to the Basics of Reliability and Risk Analysis, World Scientific, 222.