DECISION SUPPORT FOR PREVENTION AND ELIMINATION OF THE EMERGENCIES’ CONSEQUENCES BASED ON THE INFORMATION STRUCTURING FUZZY METHOD

Abstract

The article is devoted to solving the scientific problem of decision support for the prevention and elimination of emergencies’ consequences based on solving the problem of structuring information. The relevance of this task is due to the need to develop theoretical foundations for optimizing the risk of adverse effects on human health and the environment in connection with emergencies. The authors give definitions to the main terms of the studied subject area. A formalized statement of the problem to be solved is presented. A detailed emergencies’ classification with a description of the presented classes’ features is given. The system of rules for decision support in emergencies should have a multi-level hierarchy, which allows for the construction of variousdecision-making trajectories on a top-down basis. The most suitable model for building such an information space is an ontological structure that provides the creation of the necessary multi-level hierarchy, taking into account all the parameters and criteria that affect the development of the situation. The main elements of this ontological model are entities and relationships between them, the presence of which at the upper level of decomposition will indicate the risk of an emergency, and at each lower level it will expand the taxonomy of a detailed description of emergencies’ possible situations and the necessary actions to prevent or eliminate them consequences. The processing of this ontological model of rules is implemented on the basis of the structuring information fuzzy method proposed by the authors in emergencies, which differs from known analogs by the use of a new generalized criterion for optimizing the choice of decision support alternatives. The originality of the optimization formulation of the structuring problem lies in the assessment of the information elements contextual binding to a certain class of emergency situations, interdisciplinary, taking into account the presence of many links between subject areas, as well as taking into account the decrease in the level of information efficiency about the course of emergencies over time.

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Published:

2023-06-07

Issue:

Section:

SECTION III. INFORMATION PROCESSING ALGORITHMS

Keywords:

Emergencies, decision support, fuzzy rules, ontologies, classification