FEATURES OF MODELING AND FORECASTING THE DEVELOPMENT OF BANKING BUSINESS IN UKRAINE

The rapid dynamics of financial performance of banks leads to the study of the peculiarities of modeling and forecasting the development of the banking business. The negative trends of the global crisis and the spread of the pandemic are determined by the search for ways to maintain the efficient functioning of banks in the financial market. Modeling and forecasting the development of the banking business should be carried out using the tools of economic and mathematical modeling, the main feature of which is the use of indirect knowledge with the help of artificially created objects – models. To better understand the importance of modeling the development of the banking business, it is appropriate to give an example, the development and application of the wrong strategy for the development of the banking business can lead to significant problems not only in this area, including reduced liquidity of the banking system, increased problem loans, increased risk. The model of banking business development is built, which includes six equations on the main macroeconomic indicators (equation of capital and reserves of banks, equation of total assets of banks, equation of bank loans, equation of bank income, equation of bank expenses, equation of gross domestic product of Ukraine). Links between the performance of the banking sector and environmental factors, to analyze the factors influencing the development of the banking business, to forecast the dynamics of these indicators in different scenarios of economic conditions in general and the banking business in particular. The analysis of the obtained results of evaluation of the equations of the simulative model of banking business development for 2020 allowed determining that each equation of the simulative model is adequate, because the coefficients of multiple determinations take values that are close to one, including exogenous variables. To obtain the forecast values of other exogenous variables of the simulative model (the value of direct investment in Ukraine and the volume of sold industrial products) was used the method of constructing trend models, which describe the dynamics of a particular indicator (variable) over time. The forecast values of exogenous variables of the simulative model of banking business development for the I–IV quarters of 2022 are constructed. The analysis of forecast accuracy indicators showed that the value of the average absolute error (MAPE) of the amount of capital and reserves of banks in 2022 does not exceed 10% for neutral and optimistic forecasts.

Carrier-borne aircrafts aviation operation automated scheduling using multiplicative weights apprenticeship learning

Efficiency and safety are vital for aviation operations in order to improve the combat capacity of aircraft carrier. In this article, the theory of apprenticeship learning, as a kind of artificial intelligence technology, is applied to constructing the method of automated scheduling. First, with the use of Markov decision process frame, the simulative model of aircrafts launching and recovery was established. Second, the multiplicative weights apprenticeship learning algorithm was applied to creating the optimized scheduling policy. In the situation with an expert to learn from, the learned policy matches quite well with the expert’s demonstration and the total deviations can be limited within 3%. Finally, in the situation without expert’s demonstration, the policy generated by multiplicative weights apprenticeship learning algorithm shows an obvious superiority compared to the three human experts. The results of different operation situations show that the method is highly robust and well functional.

Micro downtime

Purpose Automated flow line manufacturing systems are becoming more and more relevant in industry, especially in the food and beverage sector. Improving the efficiency of automated flow line manufacturing systems is the core objectives of all companies as measured by the overall equipment effectiveness (OEE) index. The purpose of this paper is to carry out an innovative micro downtime data collection and statistical analysis in the food and beverage sector; it introduces a numerical indicator called “Cost Performance Indicator-CPI” to estimate the performance improvement of investment activities. Moreover this analysis will be used as a basis to carry out a new simulative model to study micro downtime of automatic production lines. In addition, the presented micro downtime data collection and statistical analysis will be used to construct a new simulative model to support improvement activities. Design/methodology/approach Descriptive and statistical analyses are carried out about OEE, time to repair (TTR) and time to failure (TTF) data. The least efficient production line is identified and principal causes of inefficiency are investigated. Micro downtime (downtime lower than 15 minutes) covers 57 percent of inefficiency. Investigations are carried out into the three principal machines affected by this inefficiency. The study then investigates the causes of micro downtime of these machines using ad hoc data collection and analysis. The probability distributions of TTF and TTR are evaluated and an analysis of micro downtime causes and a cause-effect is carried out. The most attractive investment in terms of recoverable OEE (1.44 percent) and costs is analyzed through the calculation of a CPI. One of the conclusions is to recommend the introduction of a payback period with a variable contribution margin. Findings This study get the basis for the construction of a new simulative model based on ad hoc micro downtime probability distributions, applied in automated flow line manufacturing systems. It gives an effort to downtime analysis in automated production lines and a guideline for future analysis. Results of this study can be generalized and extended to other similar cases, in order to study similar micro downtime inefficiency of other production lines. The statistical analysis developed could also potentially be used to further investigate the relationship between the reliability of specific machines and that of the entire line. Originality/value The case study presents a new detailed micro downtime data collection and statistical analysis in the beverage sector with the application of a numerical indicator, the CPI, in order to drive future actions. In addition, the presented micro downtime data collection and statistical analysis will be used to construct a new simulative model to support improvement activities. Moreover, results can be generalized and used as a basis for other micro downtime analyses involving the main causes of inefficiency in automated production lines.

Research of Firing Control Model of Multi-stage Synchronous Induction Coil Launcher

The problem of firing control is a critical technology of multi-stage synchronous induction coil launcher (MSSICL). Operation with high launch efficiency of MSSICL mainly depends on each stage driving coil energized when the armature moves on the proper location. In order to solve the problem of firing control for MSSICL, the firing control model of MSSICL is built based on the dynamically simulative model and the firing control criterion. The dynamically simulative model includes the voltage equations of driving circuit and the kinematic equations. The solved method is provided. In addition, the factors that influence the solved precision of the firing control model of MSSICL are analyzed.

Simulative model for evaluation of investment processes in the regions of Ukraine

To analyze and evaluate the investment processes in the regions of Ukraine, it is suggested to use a simulative model that, unlike existing ones, allows to take into account the influence of macroeconomic factors and to predict the future development of the economic system of the regions taking into account their investment potential. The examination of the assessed simulative models of the investment processes in the regions of Ukraine for adequacy is carried out using the determination coefficient and Fisher’s criterion, by which the influence of the most significant economic variables of social and economic development of the regions on the investments formation is determined. Research of the investments impact on the dynamics of economic systems indicators of the regions has shown that 86% of the constructed models are adequate. The presence of statistically significant estimates of model parameters confirms the effectiveness of the proposed approach for conducting research on the analysis and forecasting of the patterns of significant indicators formation of investment activity at the regional level, as well as their impact on indicators of social and economic development.

Risk Analysis Of Collision Between Passenger Ferry And Chemical Tanker In The Western Zone Of The Baltic Sea

This paper presents assumptions and process of the forming of a risk assessment model for collision between a passenger ferry departing from or approaching port of Świnoujście and a chemical tanker carrying a dangerous cargo. In order to assess navigational safety on the basis of data obtained from AIS system, were prepared probabilistic domains of ships, which made it possible to estimate number of navigational incidents as well as their spatial distribution, that consequently allowed to determine potentially dangerous areas. The next phase was formulation of a simulative model intended for the calculating of probability of collision between the ferry and chemical tanker as well as the determining of characteristic scenarios for such collision. This paper presents also an analysis of consequences of the collision with taking into consideration a damage of cargo tanks.