Forecasting Of Situation Research Articles

Predictive bases of development of the military sphere of national security

The methodological aspects of analysis and forecasting of military-political situation in the context of alliance building, influencing the military sphere of national security, are shown. Negative factors indicating the imbalance of global and regional security assurance system are revealed. It is emphasized that understanding of military conflict development in the form of an “escalation ladder” will allow the political and military leaders to prevent the loss of controlability of the conflict. The main trends of military and political situation determining military dangers and threats to the Union State,as well as the peculiarities of its development in the medium- and long-term forecasts were revealed. It has been specified that challenges and threats to the military security of Belarus and Russia will be of a complex and multidirectional nature, affecting all spheres of their activities. The task of their foreign and military policies is strengthening international security and strategic stability on the global and regional levels. The main features of military conflicts and armed struggle in the XXI century are defined. It is concluded that peaceful development of the Belarusian state in the conditions of increasing military violence is possible under the condition of guaranteed provision of military security of the state. It is important to continuously forecast the international and military-political situation, to improve the military organization of the state, the unity of the state power, the army and the people of the country. The main military strategic task for the political elite of the state is to deter aggression in any of its manifestations.

Experience in conducting an epidemiological analysis of dengue incidence in the Socialist Republic of Vietnam using geographic information systems

Aim: To identify regional epidemiological features of dengue fever and substantiate approaches to conducting epidemiological surveillance for this infection taking into account the regional features of its distribution and risk factors affecting its formation.Materials and methods: Retrospective epidemiological analysis of dengue incidence in the provinces of the Socialist Republic of Vietnam from 2017 to 2022. To conduct the epidemiological analysis of dengue incidence, a free version of the GIS Axioms (ГИС Аксиомы) program and the Google Earth application were used.Results: It was noted that cases of dengue fever were registered in all 63 provinces of the country, however, the dynamics of incidence levels had wide spatial and temporal ranges. Excepting Hanoi (189.6 0/0000), dengue incidence in the northern provinces are lower than those in the southern provinces. The highest average long-term incidence of dengue fever was observed in Da Nang (659.8 0/0000), Binh Duong (623.3 0/0000), Quang Binh (565.5 0/0000), Ba Ria-Vung Tau (554.6 0/0000) and Khanh Hoa (544.8 0/0000). The results of a comparative analysis of dengue incidence and the main factors influencing it in the adjacent, the incidences of dengue fever of which are significantly different from each other, are shown. The application of geoinformation systems for epidemiological analysis has been demonstrated. It has been established that the distribution of the population of Vietnam differs greatly between the administrative regions of the country, and the use of population density for epidemiological analysis and forecasting of the epidemiological situation of infectious diseases, including dengue fever, can lead to incorrect results.Conclusion: The epidemiological situation of dengue fever in Vietnam is characterized by high incidence rates, their wide ranges of spatial and temporal variability, and geographical heterogeneity. The use of GIS technologies is one of the promising approaches for epidemiological analysis and monitoring of dengue fever, as well as other infectious diseases.

Review of Epidemiological Situation on Rickettsioses in the Russian Federation in 2022 as Compared with 2013–2021, Forecast for 2023

The aim of the review was to characterize the epidemiological situation on tick-borne rickettsioses (TR) in the Russian Federation in 2022 in comparison with the pandemic years of 2020–2021 and the pre-pandemic period of 2013–2019, to give the forecast for 2023. During 2013–2022, a pattern was observed in the incidence of rickettsiosis of the tick-borne spotted fever group (with the exception of Astrakhan spotted fever – ASF), that is also characteristic of most other natural focal infections (NFIs): a sharp decrease in registered incidence rates in 2020–2021 with the subsequent increase in 2022 almost up to pre-pandemic levels or even exceedance in some regions. The absence of a defining influence of the frequency of contacts of the population with vectors on the decrease in the incidence in the period of 2020–2021 and the rise in the value in 2022 confirms the registration-related nature of the changes. Given due attention to the problem of effective detection and reporting of NFIs, we expect the incidence of tick-borne rickettsioses to remain within the confidence intervals of long-term average values in most endemic regions in 2023. Relaxed vigilance to the problem of NFIs may lead to a decline in the reported incidence of Siberian tick-borne typhus in the Krasnoyarsk and Zabaikalsky Territories, Republics of Tuva and Khakassia, Novosibirsk and Amur Regions; reduction in the incidence of ASF in Astrakhan Region. The main issue in detecting and registration of the tick-borne rickettsiosis incidence, objective assessment and forecasting of the epidemic situation as regards this group of infections is conditioned by the lack of domestic certified diagnostic test kits for laboratory verification of rickettsioses. Close cooperation between epidemiologists and clinicians is required to establish and register cases of TR based on clinical and epidemiological data.

Информационно-вычислительные ресурсы ИРНОК: инфраструктура, данные, приложения

В статье представлены этапы развития информационно-вычислительной и телекоммуникационной инфраструктуры Иркутского научно-образовательного комплекса в период с 2008 по 2022 г. Показано развитие инфраструктуры: сети передачи данных, систем хранения данных, виртуализации, вычислительных ресурсов, в том числе оборудования Иркутского суперкомпьютерного центра. Abstract The Integrated information and computing network of the Irkutsk scientific and educational complex (IICN IREC) is the basic technological platform for most interdisciplinary research conducted by scientific organizations of the Irkutsk region. The article presents the stages of development of the information, computing and telecommunications infrastructure of the IICN IREC in the period from 2008 to 2022. The main directions of modernization of IREC were: the development of a communication network, the deployment of a virtualization platform, data storage system and GPU cluster. The Irkutsk supercomputer center (ISCC) of the SB RAS, which interacts with IREC, has also been developed. The most significant stage in the development of the ISCC was the implementation of the project to create a new generation computing cluster, named after the first organizing director of the institute, Academician V.M. Matrosov. The effectiveness of the created information and computing infrastructure is shown on the example of the implementation of two major integration projects. These are the projects “Fundamental research and breakthrough technologies as the basis for the advanced development of the Baikal region and its interregional relations” (2016–2019) and “Fundamental foundations, methods and technologies for digital monitoring and forecasting of the environmental situation in the Baikal natural territory (BNT)” (2020–2022). More than a dozen institutions have taken part in these projects. To support interdisciplinary research, tools that ensure effective interaction of researchers with the IREC information and computing infrastructure have been developed at the ISDCT SB RAS. Among them are Geoportal, Digital Platform for Monitoring of BNT and Orlando Tools. As part of the projects, a large array of various formats data on the state of the region was collected and computationally complex problems were solved. The integration of heterogeneous scientific data and the possibility of processing them with high-performance computing tools open up new opportunities for obtaining new breakthrough results.

Methodological principles of analysis and forecasting of the market situation of vegetable products

The article examines the methodological principles of the analysis and forecasting of the vegetable market situation and characterizes the main types of situational research. It is argued that the analysis of the market situation should be based on interdisciplinary and systemic approaches, as well as take into account the influence of the world market of the relevant products. The system principles of the research of the market situation are highlighted and the factors of the global, external and internal environment that affect it are identified. The components of information support for monitoring the state of demand and supply are disclosed, and the main indicators and indicators characterizing the market situation are outlined. It was concluded that the research of the market of vegetable products should be based on methodological approaches that would ensure the study of the peculiarities of the formation of the product offer and its delivery to the final consumers. The factors and features of the market of the vegetable products, which must be taken into account when studying its conjuncture, are systematized. An algorithm for researching the market of vegetable products is proposed, which involves researching its market conditions, determining the capacity and purchasing behavior of consumers. It has been proven that when conducting market research of vegetable products, it is expedient to calculate the level of self-sufficiency for certain types of vegetable products. The author emphasized that when analyzing the product offer on the market of open ground vegetables, it is expedient to determine the type of competitive relations that dominate this market, and the approaches and indicators characterizing the intensity of competition are highlighted. The list of indicators that should be used to establish the regional characteristics of the vegetable market and the characteristics of the effect of its functioning, which is manifested on the basis of econommeneg.btsau.edu.ua market, economic and social efficiency, is outlined. The task of marketing analysis of the vegetable market is revealed, which involves the calculation of its potential and actual capacity and is the basis for developing forecasts of its situation. The proposed algorithm for researching the vegetable market is the portfolio analysis based on which it is possible to reasonably determine the most profitable and promising segments of the market by types of products. Key words: market of vegetable products, research of the market situation, supply and demand, intensity of competition, marketing analysis.

FORECASTING THE MECHANICAL ENGINEERING PRODUCTS MARKET OF UKRAINE: STRUCTURAL AND SALES ASPECTS

Objective. Analysis and forecasting of the market situation of machine-building products of Ukraine with a focus on structural and sales aspects. Methods. During the research, the following was applied: the dialectical method of learning processes and phenomena (for a general study of the conjuncture of the machine-building market of Ukraine); graphic (to display the dynamics of indicators of the number of enterprises and their sales volume); index (to assess the rates of growth of the investigated indicators); single-factor and multi-factor multiplicative forecasting (for forecasting sales volumes of manufactured products in general and depending on the size of production: large, medium, small and micro). Results. The analysis of the mechanical engineering market was conducted with a focus on structural and sales aspects. A tendency to reduce the number of large enterprises while preserving and moderately increasing the number of small and micro-enterprises was revealed. One-factor and three-factor multiplicative autoregressive regression models have been identified that can be used to forecast sales volumes of products of micro, small, medium and large enterprises in the machine-building industry. The forecasting of the volume of sales of products of the machine-building industry of Ukraine was carried out with the help of one-factor and three-factor multiplicative autoregression models. It was established that the accuracy of most of the obtained forecast models exceeds 90%. According to the received forecast models, it was established that the sales volume of machine-building products of small and medium-sized enterprises will grow most dynamically, while the sales volume of large enterprises will decrease.

A system based on an artificial neural network of the second generation for decision support in especially significant situations

Currently, specialized system models implemented on the basis of decision support in exceptional (emergency) situations (states) using machine learning, artificial intelligence (including using neural networks) to reproduce, predict and prevent (or minimize the risk of consequences) in exceptional situations are useful and are becoming increasingly popular. Floods also fall under such exceptional situations and states, on the basis of which the task of early forecasting of an exceptional situation arises, using the example of rising water levels at stationary hydrological posts in order to prevent (or minimize the risk) the transition of the territory management system under consideration to an exceptional state (emergency situation). To solve this problem, a decision support system is proposed for early prediction of water rise levels, based on a neural network (intelligent) analysis of retrospective data (code of a stationary hydrological post / automatic station, date, water level at a stationary hydrological post / automatic station, atmospheric pressure, wind speed, snow cover thickness, amount of precipitation, time and air temperature) in order to calculate the values of water levels for 5 days in advance. The artificial neural network itself is based on the freely distributed TensorFlow machine learning software library, and a modified error backpropagation method is used as training, the main difference of which is the addition of an artificial neural network (ANN) learning rate increase factor. A mathematical model of the subject area is constructed in the form of a multidimensional space and an integrated multidimensional data model. A single integrated model describes the subject area quite fully and can be used as a single source of information, which provides system information support, defined as a set of distributed databases. All this makes it possible to improve the accuracy of forecast values of water levels at stationary hydrological posts and automatic stations. The main difficulty in early forecasting is a sharp rise in water levels over a short period of time (usually 1 day) for various reasons. Our neural network model takes this into account and allows us to give more accurate results. The results of the analysis of the effectiveness of the method showed that the proposed decision support system is more accurate: the average error does not exceed 55.68 cm for the entire flood period, the average error between the real and calculated values in the framework of forecasting for 5 days does not exceed 2.10 % compared to existing common methods/systems (8.36 %). This will give the necessary time to special services to carry out anti–flood measures to prepare for the protection of technical facilities of enterprises.

Digital Transformation of Hazardous Geological Processes Monitoring on the Example of the Baikal Natural Territory

Baikal Natural Territory (BNT) is the territory that adjacent to Lake Baikal, which is a unique natural object and, in accordance with the UNESCO Convention, a "World Natural Heritage". Baikal is in the central part of the Baikal Rift Zone (BRZ) – the most active seismic zone located in the middle of Russia. The development of the BRZ leads to the emergence of dangerous geological processes that can lead to a violation of the balance in the Lake Baikal ecological system and the surrounding area. In addition, these processes and phenomena pose a real threat to the smooth functioning of mainline communications, hydroelectric power plants and strategically important industries in the region, which, according to the classification of the Ministry of Emergency Situations of Russia, belongs to the first category of danger. To ensure systematic monitoring and forecasting of the environmental situation of the BNT, systematic observations are organized, as well as obtaining and analysing information about the activity of hazardous geological processes in digital form. The digital transformation of monitoring of hazardous geological processes, resulting from the digitalization of processes and the development of appropriate infrastructure, provides the possibility of using new models and methods, more flexible approaches to the analysis of ongoing processes and the prediction of possible extreme events. In this paper, a digital platform is proposed that provides support for the digital transformation of the monitoring of hazardous geological processes using the example of BNT. The platform under consideration may be used for ecological monitoring of BNT area.

STATISTICAL ANALYSIS AND FORECASTING OF DEVELOPMENT OF THE MARKET OF GOODS AND SERVICES

In the article, a statistical analysis of the market of goods and services was carried out, the market situation was analyzed, the role of the calculation of elasticity indicators in demand forecasting was investigated, and factors affecting the condition, volume change and market structure were determined. When studying the patterns of market development, it was found that the calculation of market characteristics is necessary for the construction and qualitative analysis of distribution series. It has been studied that the demand in the consumer market depends on a whole set of factors, which are grouped according to the main characteristics (not including random factors). Specific methods of regional analysis are used in the analysis of the state of the market, territorial distribution of turnover and other indicators. During the research, it is necessary to study and evaluate market reactions related to trade and organizational factors, as well as distribution processes. The methodology of statistical research of the market situation of consumer goods is determined by the features of the consumer market as an object of research, the specifics of information support and economic indicators, and the corresponding set of methods of research and forecasting of the economic situation. Regulation of international trade in services has certain specificities. This is due to the fact that services have a variety of forms and content, forming a single market, which is not characterized by general features, but by general trends, which make it possible to regulate it at the global level, even taking into account new moments in its development, which TC contributes, dominating it and monopolizing it and at the same time the processes of localization separating it. Currently, the world market of services is regulated at four levels: international, sectoral,. regional and national.

Evidential policy in the management decision making mechanism at the macro level

The article presents a comparative analysis of alternative approaches to the formation of state economic policy in the modern world — purely ideological, political-conjunctural and scientific-evidential ones disclosing the unconditional advantages of the latter. Evidential economic policy that comprehensively assess available options for achieving high-priority macroeconomic goals is seen as a way to counter real-world threats to management decision-making at the macro level, based only on the ideological leanings of political parties and their theorists (classics and Keynesians), as well as the fact that opportunistic politicians persistently serve not the public interests, but their own selfi sh ones. Contributing to the formation of the methodological foundations of evidential economic policy, the author emphasizes the need to not limit oneself to careful collection of real facts, to formation of a "register of best practices" in world economic history and to the use of modern econometric methods in order to avoid reproaches in empiricism. Absolute emphasis in this case should be made on identifying cause-eff ect relations in the economic system in their strong correlation. Thus, success in the implementation of the evidential economic policy of the country is mostly associated with the state of macroeconomic theory, its ability to provide comprehensive analysis and scenario forecasting of the economic situation.

RADIATION SITUATION ASSESSMENT AND PREDICTION IN THE BALTIC SEA

The review is devoted to the analysis of scientific publications, as well as regulatory legal acts and documents in the field of radioecology and radiation situation assessment in the Baltic Sea. To date, certain areas of the Baltic Sea are classified as environmentally unfavorable in terms of a number of harmful (polluting) substances that have a negative impact on the environment, including radiation conditions.
 The article deals with two main aspects of radioecology problems: international and regional (Russian) within the Baltic Sea. Potentially hazardous objects and the main radioecological problems that are relevant at this time and require scientific and practical solutions have been analyzed.
 The objects of negative impact in the course of the study were taken into account generally accepted four main components with different concentrations of pollutants: water, organisms and suspended organic matter, sediments and surface film.
 Having studied and analyzed the statistical data of scientific research using the methods of generalized data processing, systematization and comparative analysis, a general conclusion about modern approaches to assessing and predicting the radiation situation in the Baltic Sea has been drawn.
 In our opinion, improving the efficiency of systems for ensuring radioecological safety is relevant at the present time and requires a constant and comprehensive analysis of its state, which may allow timely assessment and forecasting of the radiation situation in the Baltic Sea.
 Secondly, it is necessary to combine the efforts of the scientific community, public organizations and practicing professionals of industrial corporations from all countries of the region, which will increase the level of environmental safety of the Baltic Sea.

Big Data-Driven Hierarchical Local Area Network Security Risk Event Prediction Algorithm

Big data processing technology has attracted a lot of attention due to its forecasting and warning of Internet security situation. The current risk assessment system still has problems such as high false alarm rate and excessive reliance on expert knowledge in the security defense system. Based on the big data-driven principle, this paper constructs a hierarchical local area network security risk event prediction model and proposes a predictive complex event processing method. The model building process is evolved and improved on the basis of the scoring function. The establishment method of vulnerability database and vulnerability association database is introduced in detail. At the same time, the problem of the difference between the structure and identification method of the information in the information database and the vulnerability database is solved, and the effect of timely modification when the data do not match is realized. Experimental results show that the algorithm has an accuracy of 98.75% and a fault tolerance rate of 0.0035, which promotes the accuracy of the network risk assessment results based on multistage network attacks.

Computer science and geodemography: data matching and anomaly detection

For the first time, digital inequality was discovered on the example of using a new measure of information theory for socio-physical systems and LCLB calculus in relation to regions/countries/continents: New Zealand, Canada, Africa, South and North America, Australia. The identification of digital inequality was carried out on the basis of a study of open IT-platform statistics on the development of the COVID-19 pandemic in these regions/countries/continents. A conditional uncalibrated amount of information showed the best conditions for achieving favorable goals (for a person) by the "society-human-virus" system in New Zealand and in some African countries (where there is an irrationally productive way of making decisions). We draw attention to the fact that the "society-human-virus" system behaves as a single information/computing/computer system (in other words, as a sociotechnical system). Thus, the LCLB calculus used in this work can be effectively applied in pandemic computer science, as well as for highly effective forecasting of the socio-political situation in real time.

ОСОБЛИВОСТІ ВИКОРИСТАННЯ ОН-ЛАЙН ТЕХНОЛОГІЙ ПІД ЧАС ОРГАНІЗАЦІЇ ІНФОРМАЦІЙНО-ПСИХОЛОГІЧНОЇ ПРОТИДІЇ

Military affairs today acquire fundamentally new features compared to the entire past history of local and world wars. Thus, the military management system is formatted in a digital form, a significant part of human functions is transferred to artificial intelligence and machines. The development of online social networks and the globalization of the world community are actively used in the military industry not only for the purpose of implementing management processes, but also for the organization of negative informational and psychological influence on military personnel and the civilian population of the opposing party. Technologies 2.0 have organically fit into the informational and psychological format of conducting hybrid warfare, and their importance grows with each subsequent international military conflict in an arithmetical progression. With the beginning of Russia's full-scale aggression against Ukraine, the most urgent problems today are the research of informational influences and propaganda, mechanisms of their implementation and countermeasures. The main tasks of informational and psychological countermeasures are: monitoring, analysis and forecasting of the information situation, collection and generalization of data on sources of negative informational and psychological impact on personnel; neutralization of negative informational and psychological influence, counter-propaganda measures. For this purpose, official information channels designed to provide servicemen with information about changes in the socio-political and operational environment are currently being actively used. Their analysis showed that during the day, a serviceman receives from 10 to 15 different informational messages. Although our research indicates that for maximum effectiveness, the volume and frequency of such messages should not be large. The number of such messages per  channel should be limited to 5, at least that's what 83 % of the respondents we surveyed said.

Effect, Challenges, and Forecasting of COVID-19 Situation in India Using an ARMA Model

The world has been horribly affected by an invisible danger named COVID-19. Most of the countries are fighting against this virus, and this virus has already claimed way too many lives. In countries such as the United States, Spain, and Italy, the scenario is worse. This article first explores the complete scenario of COVID-19 in India and then discusses its effect on the Indian economy, society, and financial sector, using a mathematical model known as ARMA-autoregressive moving average model. The forecast is that India is also on the verge of facing a worst situation if it is not strictly managed by the Indian government. Of the many sectors affected by the virus, a few are discussed here supported by graphical results. The Results section includes the forecast, which illustrates that the number of infected patients can increase up to 1 400 000 till December 2020. The forecast for daily encountered cases may also go up to approximately 14 000. This article shows the impact of COVID-19 on India in the upcoming months.

OVERVIEW AND ANALYSIS OF METHODS FOR MODELING THE EPIDEMIC DEVELOPMENT PROCESS

Today, the urgent problem facing humanity is the problem of fighting epidemics and pandemics. One of the ways to solve this problem is the use of mathematical methods for predicting the pandemic process and assessing the impact of measures taken by health authorities to reduce the rate of development of the disease. Based on the analysis of a variety of information sources, the article considers the most effective approach to mathematical and computer modeling of the development of the epidemic on the basis of individually oriented and multi-agent approaches. The analysis of the problem of modeling the development of epidemics on the basis of a multi-agent approach, as well as the possibilities of predicting the course of the epidemiological process is carried out. An example of the structure of a multicomponent simulation model based on the generally accepted verbal model of the spread of viral diseases is given. As an example, the methodology of simulation agent-based modeling using the Any Logic software product of distribution processes 2019-nCoV is considered. The obtained averaged indicators confirmed the main hourly average periods of infection, which were obtained by purely statistical methods. Based on the analysis of published works, the possibilities of managing the development of the epidemic by influencing these factors have been investigated. A relatively simple method of mathematical modeling and forecasting of the epidemic situation has been proposed. It is shown that a timely and adequate forecast is a prerequisite for planning the structure, scale, timing of the necessary measures aimed at preventing epidemics and outbreaks of disease, as well as reducing and eliminating their negative consequences.
 Keywords: agent simulation, epidemic, math modeling, pandemic, prognostication, simulation.

Forecasting of the COVID-19 pandemic situation of Korea.

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/susceptible infected recoverd (SIR), agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020‒December 31, 2020 and January 20, 2020‒January 31, 2021) and testing data (January 1, 2021‒February 28, 2021 and February 1, 2021‒February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values’ comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

Simulation modeling of taxpayers’ behavior on the labor market in Ukraine

The article analyzes some components of the shadow economy using the example of modern Ukraine. The purpose of article is to predict the behavior of the economically active population when choosing an employment option using an agent-based simulation model. The work uses the methods of theoretical generalization, retrospective analysis – to study the theoretical aspects of socio-economic relations at the enterprise; system analysis, agent-based modeling – to develop a decision-making model in the labor market. The proposed algorithm of taxpayer behavior is based on studies of domestic and foreign scientists in the field of shadow economy and informal employment. Particular attention is paid to the national economic mentality as an important factor which determines the trajectory of the country’s development. As a substantiation of the subject’s behavior on the labor market, it is proposed to use the model of decision-making by a taxpayer, developed by M. Ellingham. When constructing an algorithm for the behavior of an employee, the demographic situation in Ukraine, the causes and consequences of labor migration, and the mental characteristics of the population were analyzed. The novelty of the proposed model lies in the fact that it takes into account the dependence of the taxpayer’s utility curve on the taxpayer’s age. The developed model was applied to forecasting of the demographic situation in Ukraine, and to estimation of the population participation in the informal economy sector.

Fire and explosion measures for tanks protection selection algorithm based on quantitative assessment of big breathing

Research objective: Scientific substantiation and development of an algorithm for selecting reservoir fire protection measures based on the big breathing (filling loss) quantitative assessment. Method of research: Theoretical generalization and analysis of approaches for choosing big breathing volume calculating methods, comparative analysis of modern methodological approaches for tank breaths quantitative assessment, as well as using methods for calculating BLEVE effect probability. Results of the study: Analysis of approaches for choosing methods showed that each method has its own calculation specifics, which are reflected in results. Using a comparative analysis of methodological approaches was determined that volumes of big breathing calculated for each method differ by more than 30%. In this regard, algorithm for choosing calculation methods with further forecasting of fire situation is proposed. The algorithm consists of three stages. At the beginning, it is necessary to calculate the filling loss volume, on the basis of them the level of damaging factors is carried out. Depending on the possible situation, protective measures are choosing.

Use of information technologies as a factor of the quality of life in the Republic of Bashkortostan

This article is dedicated to studying the consumption of Internet in Russia. The author analyzes the dynamics of consumption of global network by regions of the Russian Federation. Special attention is paid to the use of Internet by population of the Republic of Bashkortostan. Comparative analysis is conducted to the situation in Bashkortostan overall, as well as urban and rural areas in particular. Attention is also focused on the correlation between two indicators: “Use of the Internet” and “Assessment by households of their financial situation”. The conclusions are structured on the analysis of relevant Russian and foreign publications covering the topic of the use of Internet, as well as statistical data for the period from 2010 to 2018 (based on the materials of the Russian Federal State Statistics Service and Bashkortostan Regional Statistics Service). The conducted research allowed determining the connection between the use of Internet and assessment by the households of their financial wellbeing. The acquired data can be used in forecasting of economic situation in the region, as well as carry applied relevance for commercial organizations, for the more efficient interaction with the consumers and improvement of goods and services.