Перегляд за Автор "Pysarenko, A."

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    Learning rate in the reinforcement learning method for unknown location targets searching system
    (КПІ ім. Ігоря Сікорського, 2023) Albrekht, Y.; Pysarenko, A.
    The article explores the dependence of the system learning rate on the number of mutually independent modules in the reinforcement learning method. The study defines an environment with two types of objects that bring points to the final score and uses Deep Q Learning algorithms with 36 input data and 5 possible outcomes to conduct the experiment. The goal is to determine the optimal number of objects for which the use of reinforcement learning will give the best result for the same number of iterations. The research is part of a solution to the problem of creating a drone flock control system to find the position of objects in an unknown area.
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    Practical application of the knowledge graph on the example of developing an algorithm for creating an individual tour text
    (КПІ ім. Ігоря Сікорського, 2021) Kulbaka, N.; Lishchuk, K.; Pysarenko, A.
    The subject of the article is the practical application of the knowledge graph and methods of morphological analysis on the example of the problem of developing an algorithm for the creating an individual tour text, which is necessary for the work of a virtual guide and conducting virtual tours with exhibitions. An example of usage of the knowledge graph is demonstrated as a method for studying unstructured data, the procedure for constructing a knowledge graph from the text and the formal process of building an excursion are described. Аn assessment of the quality of the data are provided with the example of the knowledge graph of the excursion.
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    Preprocessing of audio data for voice transcription systems
    (КПІ ім. Ігоря Сікорського, 2023) Drahan, M.; Pysarenko, A.
    Voice messages are currently a powerful data collection tool. The aim of the study is to speed up the transcription of audio files. To achieve the goal, it is suggested to use a bandpass filter with a lower passband frequency in the range of 150-200 Hz and an upper passband frequency in the range of 3500-7000 Hz. The success of the system is based on the selection of the filter that optimally speeds up the transcription of audio files.
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    Software for virtual tours
    (КПІ ім. Ігоря Сікорського, 2021) N. Kulbaka, A.; Pysarenko, A.; Bondarenko, O.
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    Software for virtual tours
    (2021-12-15) Kulbaka, N.; Pysarenko, A.; Bondarenko, O.
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    Unknown location targets searching system in known environment using reinforcement learning
    (КПІ ім. Ігоря Сікорського, 2023) Albrekht, Y.; Pysarenko, A.
    This article investigates two different approaches to searching for objects of a certain type in a known environment: with a centrally controlled system using individual modules that transmit information and by dividing the entire search area into smaller ones and using individual objects. The article conducts experiments using reinforcement learning algorithms to compare the learning speed and capabilities of a system with search modules and centralized control and a separate object to search for static objects with random locations in a known environment and to search for objects moving at a constant speed in a known environment. The article provides detailed information about the experimental design, including the definition of the parameters for reinforcement learning and the size of the input and output data for the neural network. The results of the experiments are presented graphically, demonstrating the effectiveness of reinforcement learning and the difference in the learning speed and capabilities of the two systems under study.