Introduction. An overview of research in the field of classification as a method of machine learning is given. Articles containing mathematical models and algorithms for classification were selected. The use of classification in intelligent management decision support systems in various subject areas is also relevant. Goal and objectives. The purpose of the study is to analyze papers on the classification as a machine learning method. To achieve the objective, it is necessary to solve the following tasks: 1) to identify the most used classification methods in machine learning; 2) to highlight the advantages and disadvantages of each of the selected methods; 3) to analyze the possibility of using classification methods in intelligent systems to support management decisions to solve issues of forecasting, prevention and elimination of emergencies. Methods. To obtain the results, general scientific and special methods of scientific knowledge were used - analysis, synthesis, generalization, as well as the classification method. Results and discussion thereof. According to the results of the analysis, studies with a mathematical formulation and the availability of software developments were identified. The issues of classification in the implementation of machine learning in the development of intelligent decision support systems are considered. Conclusion. The analysis revealed that enough algorithms were used to perform the classification while sorting the acquired knowledge within the subject area. The implementation of an accurate classification is one of the fundamental problems in the development of management decision support systems, including for fire and emergency prevention and response. Timely and effective decision by officials of operational shifts for the disaster management is also relevant. Key words: decision support, analysis, classification, machine learning, algorithm, mathematical models.
The article is devoted to the issue of taking into account the environmental factor in the evaluation and selection of infrastructure projects that are financed with the involvement of funds from the Russian National Wealth Fund. The purpose of the study is to improve the scientific and methodological base for the assessment and selection of infrastructure projects in the face of modern environmental challenges and threats. The work used universal and general scientific methods, methods of empirical and theoretical scientific knowledge, as well as special methods, due to the essence of the object and subject of research. The developed scientific and methodological foundations and proposals for the legal regulation of the assessment and selection of infrastructure projects, taking into account the environmental factor, are presented.
Introduction. The article analyzes the use of modern information resources and systems in extinguishing wildfires. The approach uses a network-centric system for modern resources and systems integration. Goals and objectives. The purpose of the study is to identify and improve methods and tools for assessing forest fire prevention based on the integration of information resources and systems. Methods. Information-based methods and systems that allow simultaneous analysis of multi-dimensional data using digital maps, simplify the prediction and assessment of the complex effects of forest fires are considered, make it possible to quickly identify the anomalies and take the necessary measures to eliminate them. Results and discussion. Based on the results of the analysis, a generalized structure of the forest fire monitoring system was developed using a network-centric approach. Conclusion. A network-centric monitoring system combines all information resources and systems at all levels and directions. Early monitoring of the current situation, analysis of current operational information about identified thermal points, and modeling of possible scenarios for the development of the situation allows the most effective approach to solving problems of protecting the population and territory from the consequences of forest fires. Combining the advantages of individual modern technologies into a single distributed network-centric system makes it possible to effectively implement the elimination of the consequences of all types of emergencies. Key words: network-centric system, forest fires, forecasting and prevention of emergency situations, information resources and systems.
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