The subject matter of the article is an air pollution control process. The aim is development of proposals for the synthesis of the air pollution control system based on hyperconvergent infrastructures. The objectives are: the development of a mathematical model for constructing pollutants concentration fields; substantiation and development of a conceptual model of the geoinformation system for air pollution control, justification and selection of the basic infrastructure of the control system. The methods used are: system analysis of risks, cause-and-effect analysis, statistical methods. The following results are obtained: The basic influencing on character of dispersion and distribution of harmful substances factors in atmosphere are allocated. A multifactorial mathematical model has been developed for constructing fields of concentration of pollutants, which is based on two types of distribution-the normal and S L -distribution of Johnson. The geoinformation technology (GIT) structure components are determined. A program for determining the stability class of the atmosphere has been developed. A model of the process under investigation on a cartographic basis was developed with the presentation of the results in the form of a concentration isotype. The structure of the database of the parameters of sources and characteristics of sources of air pollution, which is part of the serving hyperconvergent infrastructure, has been developed. Conclusion. The synthesized air pollution control system will allow to solve such tasks: collection of primary information, its systematization, analysis and formation of a data bank; processing and presentation of data in the form of thematic pollution maps; Assessment of the current state of the environment and forecast; analysis of the causes of observed and probable changes in the state; prompt provision of necessary information to all stakeholders. K e ywor d s : air pollution; control; hyperconvergence; model.
The subject matter of the article is semantic networks of distributed search in e-learning. The goal is to synthesize a decision tree and a stratified semantic network that allows network intelligent agents in the e-learning to construct inference mechanisms according to the required attributes and specified relationships. The following results are obtained. The model of the base decision tree in elearning is suggested. To simulate the decision tree in e-learning, the logic of predicates of the first order was used, which enabled making calculations both at the nodes of the tree and at its edges, and making decisions based on the results of calculations; applying partitioning operations to select individual fragments; specifying the solutions with further expanding the inference upper vertices; expanding the multi-level model vertically and horizontally. At the first stage of the model formalization, the graph of the base decision tree was constructed, whose nodes represent a substructure capable of performing an autonomous search subtask. The second stage is filling the base tree with semantic information and organizing its interaction with network intelligent agents. To provide the tree branches of decisions in e-learning with information, the process of stratified expansion of the base decision tree was suggested where the components of the decision node were detailed and the links among the received sub-units were established both on the horizontal and on the vertical levels. It is shown that in order to establish a set of goals and search problems on the studied structure, it suffices to determine: the graphs of goals and search problems for each node type; a set of edges that determine the dependence of the execution of search targets for the nodes that are not of the same type; a set of pointers that establish probable relationships for redistributing resources in accordance with the requirements of intelligent agents; communication mapping. The developed mathematical model of the base decision tree enabled a stratified expansion. Determining intensions and extensions allowed stratified semantic networks to be used for searching. Conclusions. The method of synthesizing a decision tree and a stratified semantic network is suggested; this method enables considering them as closely interrelated ones in the context of distributed search in elearning. As a result, the process of searching and designing inference mechanisms can be formalized by the network intelligent agents according to the required attributes and given relationships.
Context. The problem of rational allocation of medical facilities of inhabited locality was considered. Methods of evaluating the effectiveness of using the existing medical network and finding ways to improve it when implementing urban development projects were proposed. Objective. The goal of the work is to build and study the procedure for solving the problem of placing medical facilities, considering the existing infrastructure of the city to fulfill the accessibility requirements. Method. A set of factors that affect the placement of a medical facilities and allow a systematic and reasonable decision to be made in choosing a location has been formed. A method for solving the problem of the location of medical facilities, providing an increase in their accessibility level considering the population, its spatial distribution, existing in the settlement of road junction and traffic congestion is proposed. The procedure for solving the problem is presented in the form of an IDEF0 model. The method is based on geoinformation analysis of data, the results of which by spatial clustering are presented in the form of a set of cartographic models, the aggregate of which allows to form a decision about the location. The method allows to assess the accessibility level of existing medical facilities in the inhabited locality, create a list of places for their possible location, find areas of the locality that are not in the access zone. Results. The method of choosing the location of the medical center has been improved, which makes it possible to make decisions based not only on the shortest distance from the center to the patient, but also on the level of its accessibility. For the first time, the structure of information technology for multivariate analysis of a network of city medical centers for decision support systems using GIS technologies is proposed. Conclusions. The medical facilities location problem, which is in increasing the level of accessibility by expanding the area of medical coverage of the territory in which the city population lives by using GIS was practically fulfilled as an IDEF0 model that defines the procedure for solving the problem and choosing the location of the medical center. The practical significance of obtained results has been proven on a practical example-an analysis of the existing hospital system for the provision of emergency medical care in Kharkiv.
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