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Документ Application of heterogeneous ensembles in problems of computer system state identification(Національний технічний університет "Харківський політехнічний інститут", 2023) Hornostal, Oleksii; Gavrylenko, SvitlanaThe object of the study is the process of identifying anomalies in the operation of a computer system (CS). The subject of the study is ensemble methods for identifying the state of the CS. The goal of the study is to improve the performance of ensemble classifiers based on heterogeneous models. Methods used: machine learning methods, homogeneous and heterogeneous ensemble classifiers, Pasting and Bootstrapping technologies. Results obtained: a comparative analysis of the use of homogeneous and heterogeneous bagging ensembles in data classification problems was carried out. The effectiveness of various approaches to the selection of base ensemble classifiers has been studied. A method for identifying the state of a computer system, based on the heterogeneous bagging ensemble was proposed. Experimental studies made it possible to confirm the main theoretical assumptions, as well as evaluate the efficiency of the constructed heterogeneous ensembles. Conclusions. Based on the results of the study, the method for constructing a heterogeneous bagging ensemble classifier, which differs from known methods in the procedure for selecting base models was proposed. It made possible to increase the classification accuracy. Further development of this research could include the creating and integration of dissimilarity metrics as well as other quantitative metrics for a more accurate and balanced base model selection procedure, which would further improve the performance of the computer system state classifier.Документ Development of a method for identifying the state of a computer systemusing fuzzy cluster analysis(Національний технічний університет "Харківський політехнічний інститут", 2020) Gavrylenko, Svitlana; Chelak, Viktor; Hornostal, Oleksii; Vassilev, VelizarThe subject of this article is the study of methods for identifying the state of computer systems. The purpose of the article is to develop a method for identifying the abnormal state of a computer system based on fuzzy cluster analysis. Objective: to analyze methods for identifying the state of computer systems; to conduct research on the selection of source data; to develop a method for identifying the state of a computer system with a small sample or fuzzy source data; to investigate and justify the procedure for comparing fuzzy distances between grouping centers and clustering objects; to develop a software and test. The methodsused in the paper: cluster analysis, fuzzy logic tools. The following resultswere obtained: a method was theoretically substantiated and investigated for identifying the state of a computer system with a small sample or fuzziness of the initial data, which is distinguished by the use of the method based on fuzzy cluster analysis by the refined grouping procedure. To solve the clustering problem, we used a special procedure for comparing fuzzy distances between grouping centers and clustering objects. Software was developed and testing of the developed method was performed. The quality of classification based on the ROC analysis is assessed. Conclusions. The scientific novelty of the results is as follows: a study was conducted on the selection of source data for analysis; a method for identifying the state of a computer system based on fuzzy cluster analysis using a special procedure for comparing fuzzy distances between grouping centers and clustering objects has been developed. This allowed to improve the classification quality to 22 %.Документ Identification of anomalies in the behavior of a computer system using fuzzy cluster analysis(ФОП Тарасенко В. П., 2019) Hornostal, Oleksii; Gavrilenko, Svitlana