MODELS OF INFORMATION-ANALYTICAL SYSTEM OF DECISION-MAKING SUPPORT CONCERNING ENVIRONMENTAL SAFETY MANAGEMENT
Journal Title: Вісник Кременчуцького національного університету імені Михайла Остроградського - Year 2018, Vol 1, Issue 109
Abstract
Purpose. To create fuzzy model of situation recognition which allows to correct and replenish the knowledge base and generate reports and recommendations for correction of the environmental situation or taking measures for environmental safety. Methodology. Elements of the theory of fuzzy logic and fuzzy sets and methods of system analysis are used to design and describe the composition and structure of the IAS. Results. The theoretical multiplicity model of IAS of atmospheric air environmental monitoring at the municipal level is proposed, which includes the subsystem of the urbosystem parameters monitoring, decision-making support, the information complex "parameters database - situation knowledge database". A model for identifying problem and environmentally hazardous situations is developed. The structure of operational information is based on the analysis and classification of situations (qualitative assessments of the state of the process, based on the analysis of environmental parameters). Originality. The theoretical multimodel IAS of atmospheric air environmental monitoring at the municipal level has been developed, which includes the subsystem of the urbosystem monitoring parameters, decisionmaking support, information system "parameters database - situation knowledge database" and allows operatively to recognize environmentally hazardous situations and to make adequate decisions on their correction. Practical value. In the case of implementation of the above-mentioned components of IAS at the municipal level, a basis for an integrated monitoring system will be formed, which will ensure its effectiveness. The presence of branched direct interconnections of the subsystems in the complex should ensure the unity of the monitoring system for rational implementation of the tasks.
Authors and Affiliations
V. Baharev, I. Shevchenko, S. Koval, O. Kortsova, А. Marenych
Keywords
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- EP ID EP659679
- DOI 10.30929/1995-0519.2018.2.p1.72-79
- Views 49
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