DIGITAL RISK ASSESSMENT AND PREDICTION IN TECHNOLOGY PROCESS STAGES OF ORE-STREAMS
Soltan A.M. Kopzhassarov B.T. Belginova S. Vais Y.A. Azamatova Z. Khassenova Z.T.
15 February 2023Little Lion Scientific
Journal of Theoretical and Applied Information Technology
2023#101Issue 31322 - 1332 pp.
The goal of the work is to improve the quality of the management process by quantifying and predicting management and decision-making risks in multi-parameter systems, using ore streams as an example. The key to the ore management system in the paper is the control process. The control process appears to be a complex procedure involving measurement procedures, comparison of the measured value with the standard and decision-making. Under conditions of parametric uncertainty of control agents, control is accompanied by decision-making errors in the form of false and undetected rejects. In the true context, probable errors are defined as two types of risk: manufacturers risk and clients risk. To quantify these risks, probabilistic and simulation models have been developed to investigate the impact of statistical characteristics of control agents and simulations on control outcomes. The validity and effectiveness of the modelling is tested with a computer experiment. The modelling approach developed is universal and can be used in a variety of scientific and technical practical applications. The authors have proposed a new multiapproach methodology for quantifying decision-making risks in a multi-parameter control system.
Agent , Control , Credibility , Error , Management , Model , Norm , Probability , Process , Risks , System
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School of Information Technology and Intelligent Systems, EKTU named after D. Serikbayev Non-profit JSC, 19 Serikbayev street, Ust-Kamenogorsk city, 070003, Kazakhstan
Department of Computer Modelling and Information Technology, EKU named after S. Amanzholov Nonprofit JSC, 34 30th Guards Division street, Ust-Kamenogorsk city, 070002, Kazakhstan
University Turan, 16a Satbayev street, Almaty city, 050013, Kazakhstan
Schools of Metallurgy and Mineral Processing, EKTU named after D. Serikbayev Non-profit JSC, 19 Serikbayev street, Ust-Kamenogorsk city, 070003, Kazakhstan
School of Information Technology and Intelligent Systems
Department of Computer Modelling and Information Technology
University Turan
Schools of Metallurgy and Mineral Processing
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