Intelligent Technologies in Decision-Making Support Systems

Abstract

Continuous automation, which excludes a person from control systems, often leads to unpredictable consequences. However, for complex large-scale man-machine complexes and technological facilities with an increased risk of operation, it is required to create information support systems for decision-making for decision-makers. The article discusses some issues of building a new generation of information support systems for decision-making to improve the efficiency and safety of the functioning of human-machine control systems (HMCS) and production facilities. The application of neuro-fuzzy logics and adaptive methods of modeling and management as intelligent tools for building information support systems for operational personnel is considered. A new hybrid method for assessing and predicting the states of weakly formalized and fuzzy systems is proposed, based on a neuro-fuzzy model and effective algorithms for adaptive identification.