Кафедра "Комп'ютерна математика і аналіз даних"
Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/7570
Офіційний сайт кафедри http://web.kpi.kharkov.ua/kmmm
Кафедра "Комп'ютерна математика і аналіз даних" заснована в 2002 році.
Кафедра входить до складу Навчально-наукового інституту комп'ютерних наук та інформаційних технологій Національного технічного університету "Харківський політехнічний інститут", забезпечує підготовку бакалаврів і магістрів за проектно-орієнтованою освітньою програмою за напрямом науки про дані "DataScience".
У складі науково-педагогічного колективу кафедри працюють: 3 доктора наук: 1 – технічних, 1 – фізико-математичних, 1 – педагогічних; 15 кандидатів наук: 10 – технічних, 4 – фізико-математичних, 1 – педагогічних; 3 співробітників мають звання професора, 9 – доцента.
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Документ Dynamic problem of formation of securities portfolio under uncertainty conditions(Scientific Route, Estonia, 2019) Raskin, Lev; Sira, Oksana; Katkova, TetianaThe analysis of known methods for solving the problem of forming a portfolio of securities in the face of uncertainty is carried out. Traditionally, the problem is solved under the assumption that for each type of asset, the values of the main statistical characteristics of the random value of their profitability (mathematical expectation and variance) are known. At the same time, the variance of portfolio returns, which is minimized, is used as a criterion for portfolio optimization. Two alternative approaches to solving the formulated problem are proposed. The first of them provides a decision on the criterion of the probability that the random total portfolio return will not be lower than the given. It is assumed that the random return for each type of asset is distributed normally and the statistical characteristics of the respective densities are known. The original problem is reduced to the problem of maximizing the quadratic fractional criterion in the presence of linear constraints. To solve this non-standard optimization problem, a special iterative algorithm is proposed that implements the procedure for sequential improvement of the plan. The method converges and the computational procedure for obtaining a solution can be stopped by any of the standard criteria. The second approach considers the possibility of solving the problem under the assumption that the distribution densities of random asset returns are not known, however, based on the results of preliminary statistical processing of the initial data, estimates of the values of the main numerical characteristics for each of the assets are obtained. To solve the problem, a new mathematical apparatus is used – continuous linear programming, which is a generalization of ordinary linear programming to the case when the task variables are continuous. This method, in the considered problem, is based on solving an auxiliary problem: finding the worst-case distribution density of a random total portfolio return at which this total return does not reach an acceptable threshold with maximum probability. Now the main minimax problem is being solved: the formation of the best portfolio in the worst conditions. The resulting computational scheme leads to the problem of quadratic mathematical programming in the presence of linear constraints. Next, a method is proposed for solving the problem of forming a portfolio of securities, taking into account the real dynamics of the value of assets. The problem that arises in this case is formulated and solved in terms of the general theory of control, using the Riccati equation.Документ Comparator identification in the conditions of bifuzzy initial data(Scientific Route, Estonia, 2021) Raskin, Lev; Sira, Oksana; Katkova, TetianaWhen solving a large number of problems in the study of complex systems, it becomes necessary to establish a relationship between a variable that sets the level of efficiency of the system’s functioning and a set of other variables that determine the state of the system or the conditions of its operation. To solve this problem, the methods of regression analysis are traditionally used, the application of which in many real situations turns out to be impossible due to the lack of the possibility of direct measurement of the explained variable. However, if the totality of the results of the experiments performed can be ranked, for example, in descending order, thus forming a system of inequalities, the problem can be presented in such a way as to determine the coefficients of the regression equation in accordance with the following requirement. It is necessary that the results of calculating the explained variable using the resulting regression equation satisfy the formed system of inequalities. This task is called the comparator identification task. The paper proposes a method for solving the problem of comparator identification in conditions of fuzzy initial data. A mathematical model is introduced to describe the membership functions of fuzzy parameters of the problem based on functions (L–R)-type. The problem is reduced to a system of linear algebraic equations with fuzzy variables. The analytical relationships required for the formation of a quality criterion for solving the problem of comparator identification in conditions of fuzzy initial data are obtained. As a result, a criterion for the effectiveness of the solution is proposed, based on the calculation of membership functions of the results of experiments, and the transformation of the problem to a standard problem of linear programming is shown. The desired result is achieved by solving a quadratic mathematical programming problem with a linear constraint. The proposed method is generalized to the case when the fuzzy initial data are given bifuzzy.Документ Formation of securities portfolio under conditions of uncertainty(Technology center PC, 2017) Sira, Oksana; Katkova, TetianaWe examined a problem on the formation of securities portfolio. A criterion for portfolio effectiveness is determined – a probability that the total portfolio profitability exceeds a threshold. In connection with real shortage of the volume of initial data, we substantiated the rejection of hypothesis about the normality of their distribution law and the problem is solved under assumption about the worst distribution density of these data. In this case, it is accepted that mathematical expectation and the dispersion of values for the cost of assets are the fuzzy numbers. The form of membership function of the fuzzy parameters in the problem is selected. We constructed an analytical expression to describe the criterion in the terms of fuzzy mathematics. In this case, a problem on the maximization of fractional-quadratic functional with linear constraints is obtained. We devised a method for solving the obtained fuzzy problem of mathematical programming, which reduces this problem to the conventional problem of nonlinear programming. In order to solve this problem, it is proposed to employ the optimization method of zero order. It is demonstrated that the portfolio risk depends quadratically on the mathematical expectation of its profitability. Recommendations are given regarding the choice of numerical value for the mathematical expectation of portfolio profitability depending on the acceptable portfolio risk.Документ Finding the probability distribution of states in the fuzzy markov systems(Technology center PC, 2017) Raskin, Lev; Sira, Oksana; Katkova, TetianaA problem on finding the stationary distributions of probabilities of states for the Markov systems under conditions of uncertainty is solved. It is assumed that parameters of the analyzed Markov and semi-Markov systems (matrix of transition intensities, analytical description of distribution functions of the durations of being in states of the system before exiting, as well as a matrix of transition probabilities) are not clearly assigned. In order to describe the fuzziness, we employ the Gaussian membership functions, as well as functions of the type. The appropriate procedure of systems analysis is based on the developed technology for solving the systems of linear algebraic equations with fuzzy coefficients. In the problem on analysis of a semi-Markov system, the estimation of components of the stationary distribution of probabilities of states of the system is obtained by the minimization of a complex criterion. The criterion considers the measure of deviation of the desired distribution from the modal one, as well as the level of compactness of membership functions of the fuzzy result of solution. In this case, we apply the rule introduced for the calculation of expected value of fuzzy numbers. The criterion proposed is modified through the introduction of weight coefficients, which consider possible differences in the levels of requirements to different components of the criterion.