The paper discusses a method for constructing a nonlinear software reliability efficiency function. The proposed algorithm is based on the use of information about the values ​​of reliability criteria, as well as some expert judgments. This approach differs significantly from previously proposed models for assessing software reliability, which are based on a probabilistic approach. In the proposed method, in addition to objective information, subjective expert assessments are taken into account, which allows for a more flexible assessment of the reliability of software products.

Keywords: software reliability, probabilistic models, statistical models, partial performance criteria, linear programming, vector optimization, decision theory

The paper describes a multifactorial nonlinear regression model of revenue dynamics of the mining and metallurgical company Severstal, based on retrospective information for 2009-2021. Production volumes by type were used as independent variables: hot-rolled and cold-rolled sheet, galvanized sheet and sheet with other metal coating, rolled products, large diameter pipes, other pipe products and profiles. The criteria of multiple definition and Fisher, as well as the average absolute approximation error, were used as criteria for the adequacy of the model. A model competition was held to select the best regression dependence. As a result, a model is constructed containing inverse transformations of two independent variables in the right part.

Keywords: regression model, least squares method, adequacy criteria, mining and metallurgical company, revenue, model competition

In the work, based on the previously constructed multifactor dynamic regression model of water level in the Iya River (Eastern Siberia), the authors forecast this indicator for June 2023 in three options: pessimistic, optimistic and neutral (base). A comparison of the forecasting results with the actual value of the water level confirmed the high adequacy of the model and good prospects for its future successful use to solve a wide range of applied and practical problems.

Keywords: regression model, river water level, lag time, seasonal variable, forecast, adequacy, criteria

The article studies the possibility of using the continuous form of the maximum consistency method when constructing regression models to calculate the forecast values of the air transport passenger turnover indicator in the Russian Federation. The method under study is compared with classical methods of regression analysis - least squares and moduli. To assess the predictive properties of the methods, the average relative forecast error and the continuous form of the criterion for the consistency of behavior between the calculated and actual values of the dependent variable are used. As a result of the analysis, a conclusion was made about the possibility of using the method under study to solve forecast problems.

Keywords: least squares method, continuous form of the maximum consistency method, modeling, passenger turnover, air transport, adequacy criteria

The paper presents a brief overview of publications describing the experience of using mathematical modeling methods to solve various problems. A multivariate piecewise linear regression model of a steel company was built using the continuous form of the maximum consistency method. To assess the adequacy of the model, the following criteria were used: average relative error of approximation, continuous criterion of consistency of behavior, sum of modules of approximation errors. It is concluded that the resulting model has sufficient accuracy and can be used for forecasting.

Keywords: mathematical modeling, piecewise linear regression, least modulus method, continuous form of maximum consistency method, steel company

The paper presents a refined regression model of water level dynamics in the Siberian river Iya, which includes six natural factors on the right side (the number of days with precipitation in the Sayan Mountains, average day and night temperatures for the month, the amount of precipitation, snow depth, average atmospheric pressure for the month ) taking into account the delay, as well as a specially generated seasonal variable. The high adequacy of the model is indicated by the values ​​of the criteria of multiple determination, Fisher, and the average relative error of approximation. The constructed model can be effectively used to solve a wide range of forecasting problems.

Keywords: regression model, river water level, lag time, seasonal variable, forecast

Analyses for the current publishes show that the problem of forecast water overflowing is actual and often causing a lot health threaten and other dangerouses. This article offers computing, analysis and development the regression model of the level of Ia river. The final model correspont the real data with proper level. The final calculation means that this model could be used for real forecast for defend the people from water's overflow.

Keywords: model, simulation, river, water level, flood, emergency, forecast, statistics, monitoring, analysis, iya river, Irkutsk region

Social and pension provision are key processes in the activities of any state, and the issues of forecasting expenses for them are among the most important in the economy. The task of evaluating the effectiveness of the pension fund has been solved by various methods, including regression analysis methods. This task is particularly difficult due to the presence of a large number of factors determining the activity of the pension fund, such as: the number of recipients of old-age pensions, the number of policyholders, self-employed policyholders, recipients of benefits, insured persons and working pensioners. As the main approach to the study, the method of implementing a model competition was applied. Those variants that violated the meaningful meaning of the variables and did not fully reflect the behavior of the modeled process were excluded from the resulting set of alternative model options. The final option was selected using the multi-criteria selection method. It is revealed that the use of relative variables is important for qualitative modeling of the studied processes. The above model shows that an increase in the ratio of the number of employers and the self-employed to the number of insured persons leads to a decrease in the cost of financing social and pension provision.The model can be effectively used for short-term forecasting of the total annual volume of financing of the pension fund department in the context of changing social and macroeconomic factors.

Keywords: pension fund, regression model, model competition, adequacy criteria, forecasting

The paper describes the procedure for conducting a competition for regression models based on statistical data for the East Siberian Railway. At the same time, it is assumed to build a set of additive alternative versions of the model with the subsequent choice of the best option based on the involvement of a number of adequacy criteria. The unloading of wagons is singled out as the output variable of the model, and the input variables are: the average gross weight of a freight train, cases of failures of technical means of the 1st – 2nd category of operational nature, the working fleet of freight wagons. The implementation of the model competition allowed us to build over two hundred alternative options, from which the best alternative was selected using multi-criteria selection methods based in this case on a continuous criterion of consistency of behavior.

Keywords: railway transport, mathematical model, regression analysis, least squares method, model competition, adequacy criteria, multi-criteria selection

A review of publications by Russian and foreign researchers on the issues of modeling the process of assessing the degree of security of individual components of an informatization object (automated system) is presented. The main factors influencing the level of security are analyzed. The types of objects of unauthorized influence are given. The choice of the “information carrier” as the main generalized object and the list of actual threats to it are substantiated, their brief analysis is given. As the output (dependent) variable of the developed regression model, the level of information carrier security is determined. The input (independent) variables are the degree of danger of threats: illegal access to protected information; unauthorized copying of protected information; overcoming physical protection; loss of carriers of information. The developed model has the form of a regression equation and can be used to predict the level of security of information carriers.

Keywords: information security, informatization object, automated system, information carriers, information security threats, security level, regression model, expert information, adequacy criteria