DEVELOPMENT OF METHOD BASE ON FUZZY DECISION TREES FOR IDENTIFICATION OF THE COMPUTER SYSTEMS STATE
DOI:
https://doi.org/10.26906/SUNZ.2023.1.078Keywords:
computer system, state identification, data processing, machine learning, fuzzy logic, fuzzy decision treesAbstract
The subject of research is the methods and means of identifying the state of the computer system. The purpose of the article is to improve the quality of data classification by developing a method for identifying the state of the computer system. Task: to investigate methods of identifying the state of a computer system and to develop a method of classifying the state of a computer system for the purpose of data protection. Methods used: artificial intelligence methods, machine learning, decision tree methods. The following results were obtained: methods of identifying the state of the computer system KNN (k Nearest Neighbors), support vector method (SVM), neural networks, decision trees were investigated. The results were obtained: a method of identifying the state of the computer system based on of fuzzy decision trees, which differs from the known methods of fuzzy decision trees by the presence of a special procedure for falsification the attributes of source data and constructing membership function was proposed. The software was developed, in which the proposed method of solving the problem of identifying the state of the computer system was implemented and investigated. Conclusions. The scientific novelty of the obtained results lies in the study of methods for identifying the state of the computer system, the development of a method based on fuzzy decision trees, the assessment of the quality of the model at the stage of training and testing, and the performance of a comparative analysis.Downloads
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