Methods for control over learning individual trajectory

The article discusses models, methods and algorithms of determining student's optimal individual educational trajectory. A new method of controlling the learning trajectory has been developed as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects

Development of spreadsheet simulation models of gas cylinders inventory management

The solution of the problem of managing the inventory of an enterprise whose activities are related to the purchase and sale of gas cylinders is considered. To solve the problem, it was necessary to investigate and choose the best inventory management strategy that provides the minimum value of the average inventory balance in the warehouse with the established upper limit of the average deficit. The problem of determining the best strategy is presented as a discrete programming problem, the required variables of which depend on the replenishment method. With a periodic replenishment strategy, the controlled variables are the volume of the delivery line and the delivery interval, with a threshold one, the minimum inventory level and the volume of the delivery line. Let’s also consider replenishment with a predicted inventory level, where the delivery level and the minimum inventory level are used as control variables. Three tabular simulation models with a given delivery time and random demand are proposed. Using the Chi-square test, it was found that the quantity demanded has a normal distribution law. By carrying out computational experiments, the optimal values of controlled variables were determined. The best objective function values were obtained using a model with a predicted inventory level and a threshold replenishment strategy. Experiments conducted on the basis of historical data have shown the advantage of the two model strategies compared to the strategy currently used in the enterprise. The use of a model with a predictable inventory level would reduce the average inventory balance by 46 %, and, consequently, save working capital. The results of the study can be useful for managers of enterprises whose activities are related to inventory managemen

An inventory model with random demand

The article describes a three-product inventory model with random demand at equal frequencies of delivery. A feature of this model is that the additional purchase of resources required is carried out within the scope of their deficit. This fact allows reducing their storage costs. A simulation based on the data on arrival of raw and materials at an enterprise in Kazakhstan has been prepared. The proposed model is shown to enable savings up to 40.8% of working capital

The dynamic model of enterprise revenue management

The article presents the dynamic model of enterprise revenue management. This model is based on the quadratic criterion and linear control law. The model is founded on multiple regression that links revenues with the financial performance of the enterprise. As a result, optimal management is obtained so as to provide the given enterprise revenue, namely, the values of financial indicators that ensure the planned profit of the organization are acquired

Event-driven simulation of the state institution activity for the service provision based on business processes

The paper presents an approach, based on business processes, assessment and control of the state of the state institution, the social insurance Fund. The paper describes the application of business processes, such as items with clear measurable parameters that need to be determined, controlled and changed for management. The example of one of the business processes of the state institutions, which shows the ability to solve management tasks, is given. The authors of the paper demonstrate the possibility of applying the mathematical apparatus of imitative simulation for solving management tasks

Enterprise Compensation System Statistical Modeling for Decision Support System Development

This article raises the issue of decision support system (DSS) development in enterprises concerning the compensation system (CS). The topic is relevant as the CS is one of the main components in human resource management in business. A key element of such DSSs is CS models that provide predictive analytics. Such models are able to give information about how a particular CS affects output, product quality, employee satisfaction, and wage fund. Thus, the main goal of this article is to obtain a CS statistical model and its formulas for determining the probability densities of resultant indicators. To achieve this goal, the authors conducted several blocks of research. Firstly, mathematical formalization of CS functionality was described. Secondly, a statistical model of CS was built. Thirdly, calculations of CS result indicators were made. Reliable scientific methods were used: black box modeling and statistical modeling. This article proposes a statistical and analytical model. As an example, a piecework-bonus system statistical model is demonstrated. The discussion derives formulas of integral estimations showing the probability density of the resulting CS indicators and the related statistical characteristics. These results can be used to predict the behavior of the workforce. This constitutes the scientific novelty of the study, which will establish significant advances in the development of DSSs in the field of labor economics and HR management

Regrouping a pension capital investment portfolio considering transaction costs

Due to the instability of the financial market, there is a need to develop alternative methods and models investing pension savings, which would increase the efficiency of the funded component of the pension system in Russia. The authors have previously proposed the model of pension capital investment portfolio, taking into account the basic legal requirements and protecting the sub-portfolios of bonds interest rate risk including the immunization strategy into the model. The paper introduces the model that allows rebuilding the investment portfolio generated with minimal transaction costs charged by the Exchange for the purchase and sale of securities. The main aim of study is to propose the mathematical model of reforming the investment portfolio already formed, which minimizes transaction costs, based on the previously proposed models for forming the investment portfolio of pension savings; to prove that the presence of transaction costs leads to reduction of investment income according to the results obtained when using the proposed model. The method used in the study: the economic and mathematical modeling, methods of optimization, simulation. The results. The authors obtained the reorganization model of the previously formed investment portfolio. The numerical testing for the case of accounting transaction costs and without them revealed that frequent revision of the portfolio implies reduction of investment income owing to the presence of transaction costs

Regrouping a pension capital investment portfolio considering transaction costs

Due to the instability of the financial market, there is a need to develop alternative methods and models investing pension savings, which would increase the efficiency of the funded component of the pension system in Russia. The authors have previously proposed the model of pension capital investment portfolio, taking into account the basic legal requirements and protecting the sub-portfolios of bonds interest rate risk including the immunization strategy into the model. The paper introduces the model that allows rebuilding the investment portfolio generated with minimal transaction costs charged by the Exchange for the purchase and sale of securities. The main aim of study is to propose the mathematical model of reforming the investment portfolio already formed, which minimizes transaction costs, based on the previously proposed models for forming the investment portfolio of pension savings; to prove that the presence of transaction costs leads to reduction of investment income according to the results obtained when using the proposed model. The method used in the study: the economic and mathematical modeling, methods of optimization, simulation. The results. The authors obtained the reorganization model of the previously formed investment portfolio. The numerical testing for the case of accounting transaction costs and without them revealed that frequent revision of the portfolio implies reduction of investment income owing to the presence of transaction costs

Enterprise Compensation System Statistical Modeling for Decision Support System Development

This article raises the issue of decision support system (DSS) development in enterprises concerning the compensation system (CS). The topic is relevant as the CS is one of the main components in human resource management in business. A key element of such DSSs is CS models that provide predictive analytics. Such models are able to give information about how a particular CS affects output, product quality, employee satisfaction, and wage fund. Thus, the main goal of this article is to obtain a CS statistical model and its formulas for determining the probability densities of resultant indicators. To achieve this goal, the authors conducted several blocks of research. Firstly, mathematical formalization of CS functionality was described. Secondly, a statistical model of CS was built. Thirdly, calculations of CS result indicators were made. Reliable scientific methods were used: black box modeling and statistical modeling. This article proposes a statistical and analytical model. As an example, a piecework-bonus system statistical model is demonstrated. The discussion derives formulas of integral estimations showing the probability density of the resulting CS indicators and the related statistical characteristics. These results can be used to predict the behavior of the workforce. This constitutes the scientific novelty of the study, which will establish significant advances in the development of DSSs in the field of labor economics and HR management

Representation Learning for EEG-Based Biometrics Using Hilbert–Huang Transform

A promising approach to overcome the various shortcomings of password systems is the use of biometric authentication, in particular the use of electroencephalogram (EEG) data. In this paper, we propose a subject-independent learning method for EEG-based biometrics using Hilbert spectrograms of the data. The proposed neural network architecture treats the spectrogram as a collection of one-dimensional series and applies one-dimensional dilated convolutions over them, and a multi-similarity loss was used as the loss function for subject-independent learning. The architecture was tested on the publicly available PhysioNet EEG Motor Movement/Imagery Dataset (PEEGMIMDB) with a 14.63% Equal Error Rate (EER) achieved. The proposed approach’s main advantages are subject independence and suitability for interpretation via created spectrograms and the integrated gradients method