Intelligent system for adaptive selection of scenarios for parametric monitoring data divergence detection

 Y.E. Shishkin1,2, A.V. Skatkov1

 1 Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33

2 Institute of Natural and Technical Systems, RF, Sevastopol, Lenin St., 28


DOI: 10.33075/2220-5861-2019-2-37-42

UDC 004.9


     The article proposes an intelligent decision support system for choosing a statistical criterion for detecting divergence when analyzing monitoring data of complex objects and environments, taking into account the power and sensitivity of the criterion as well as the presence of risks. A scheme for selecting the parametric difference criterion depending on the size and number of samples is presented. A component of intelligent information technology has been developed that selects the optimal parametric criterion for detecting differences in monitoring data based on automatic selection of scenarios.

     The basis of the intellectualization of the decision support system for choosing criteria for distinguishing samples of monitoring data from complex objects and environments is to enter decision points that enable decision makers to determine priorities: the sensitivity or the probability of false positives, in the case when there is no Pareto-optimal solution.In the theory of decision making, the greatest complexity is caused by the formation of an evaluation matrix, the process of which is still not fully formalized and does not have a specific decision algorithm. Therefore, it was proposed to carry out the formation of an evaluation matrix based on the information scenario technology. The decision maker has some freedom in the choice of scenarios, while under the scenario this freedom is limited, this restriction can be removed by expanding the list of scenarios. It is possible to facilitate the selection of scenarios by introducing intelligent solutions based on artificial intelligence technologies and adaptation mechanisms.

     To illustrate the intellectual approach in the framework of information technology, three basic decision-making scenarios under uncertainty are considered: a minimax approach with relative estimates, direct voting and risk minimization.

Keywords: intellectualization, environment monitoring, parametric criteria, mathematical modeling, complex systems, data mining, decision support.

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