The problems of organizational risk management of industrial safety of large-scale transport systems are considered. On the basis of the large-scale security systems theory, large-scale transport systems theory, and experience in the development of large-scale industrial safety systems in transport, proposed a methodology to reduce technospheric risks using advanced intelligent mechanisms for activation of the human factor, as well as integration of natural and artificial intelligence for decision-making in the large-scale transport systems. This integration is achieved through a combination of knowledge, experience and intuition of decision makers, with the optimal procedures of adaptive identification and forecasting, learning and management that minimize risks of industrial safety of large-scale transport systems in terms of dynamics and uncertainty.
industrial safety, transportation, system, structure, network, risk, management, mechanism, intelligence, adaptation, learning
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