Development of decision support in the structure of the information­analytical system of atmospheric air environmental monitoring

Abstract

The main problem that determines the efficiency of environmental monitoring systems is the lack of validity of management decisions on correction of environmental situations. In such conditions, a formal versatile basis that describes the information-analytical system (IAS) of environmental monitoring is required.For the development and description of the IAS composition and structure, elements of the theory of fuzzy logic and fuzzy sets and methods of system analysis are used. Thus, the theoretical basis for the development of a versatile IAS structure of environmental monitoring is formed. The set-theoretical model of the information-analytical system of environmental monitoring of atmospheric air at the municipal level, which includes subsystems of the urban system parameter monitoring, decision support, the information system “parameter database - situation knowledge base” is proposed.The decision support subsystem is presented as the decision model that determines the allowable transformations of situations and a set of strategies for applying these transformations to solve the problem of eliminating an adverse situation. The adaptive fuzzy model of situation recognition in the process of environmental monitoring, which allows producing diagnostic conclusions is developed. The diagnostic process is represented by a sequence of actions, which involves three steps: determining the criticality for each situation feature; determining the degree of criticality; providing linguistic features. The advantage of the proposed IAS architecture is the possibility of fast scaling of the decision support system. This is achieved by simply expanding the feature and situation dictionary and the knowledge base, as well as the flexible configuration of the knowledge base by correction of weight ratios of elementary premises of the rules. The general description of the information technology of monitoring and support of operational decision-making on correction of environmentally hazardous situations is formed. The results of setting the fuzzy model of situation recognition by means of experimental learning of the system on the examples – specific results of observations of atmospheric air quality are obtained. The self-learning ability of the system is found, which ultimately will allow limiting the involvement of real individuals as experts in the assessment of environmental situations by automating the diagnostic process