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Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/35393
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6 результатів
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Документ Stock market statistical data analysis for prices forecasting and trading decision support(Dana, Italy, 2021) Грінберг, Галина Леонідівна; Grinberg, GalinaA general problems and methods for stock market statistical analysis are analyzed. A new method for stock price forecasting problem is considered based on a time series structural decomposition approach realized in special assignment of wave component auto-regression model as a superposition of harmonics with tuning frequencies. Computer simulation has been fulfilled in order to evaluate the performance of proposed method and algorithms.Документ Preference Function Reconstruction for Multiple Criteria Decision Making Based on Machine Learning Approach(Springer International Publishing, 2014) Lyubchyk, Leonid; Grinberg, GalinaThe problem of expert preference function reconstruction in decision making process of multicriterion comparative assessment of set of object is considered. The problem is reduced to integral indicator identification using available data of object’s performance indexes measurements as well as expert estimation of integral indicators values for each object and feature weights. Based on machine learning approach and expert estimations concordance technique, the solution of preference function recovering problem is obtained in the form of optimal nonlinear object feature convolution.Документ Nonlinear dynamic system kernel based reconstruction from time series data(ТВіМС, 2015) Lyubchyk, Leonid; Kolbasin, Vladislav; Grinberg, GalinaA unified approach to reccurent kernel identification algorithms design is proposed. In order to fix the auxiliary vector dimension, the reduced order model kernel method is proposed and proper reccurent identification algorithms are designed.Документ Inverse Dynamic Models in Chaotic Systems Identification and Control Problems(2018) Lyubchyk, Leonid; Grinberg, GalinaInverse dynamic models approach for chaotic system synchronization in the presence of uncertain parameters is considered. The problem is identifying and compensating unknown state-dependent parametric disturbance describing an unmodelled dynamics that generates chaotic motion. Based on the method of inverse model control, disturbance observers and compensators are synthesized. A control law is proposed that ensures the stabilization of chaotic system movement along master reference trajectory. The results of computational simulation of controlled Rösller attractor synchronization are also presented.Документ Ranking Model Real-Time Adaptation via Preference Learning Based on Dynamic Clustering(ННК "IПСА" НТУУ "КПI iм. Iгоря Сiкорського", 2017) Lyubchyk, Leonid; Galuza, Oleksy; Grinberg, GalinaThe proposed preference learning on clusters method allows to fully realizing the advantages of the kernel-based approach. While the dimension of the model is determined by a pre-selected number of clusters and its complexity do not grow with increasing number of observations. Thus real-time preference function identification algorithm based on training data stream includes successive estimates of cluster parameter as well as average cluster ranks updating and recurrent kernel-based nonparametric estimation of preference model.Документ Nonlinear expert preference function concordance identification for multiple criteria decision making(ТВіМС, 2014) Lyubchyk, Leonid; Grinberg, GalinaThe proposal generalization of expert estimates concordance idea for the case of nonlinear preferance function guaranties on optimal concordance of mesuarement and expert data, whereas machine learning approach ensure the possibility of more accurate approximation expert preference function with complex structure.