Перегляд за Автор "Likhouzova, T."

Зараз показуємо 1 - 11 з 11
  • Ескіз
    ДокументВідкритий доступ
    An architectural solution for data collection and monitoring system software
    (КПІ ім. Ігоря Сікорського, 2021) Tymchenko, O.; Likhouzova, T.
  • Ескіз
    ДокументВідкритий доступ
    Automatic system of extraction and consolidation of data from digital images
    (КПІ ім. Ігоря Сікорського, 2020) Korzun, I.; Likhouzova, T.
  • Ескіз
    ДокументВідкритий доступ
    Improving the efficiency of distributed data warehouses
    (КПІ ім. Ігоря Сікорського, 2022) Mamuta, M.; Likhouzova, T.
  • Ескіз
    ДокументВідкритий доступ
    Models for analysis of water suitability
    (КПІ ім. Ігоря Сікорського, 2023) Makarchuk, L.; Likhouzova, T.
    The problem of unsuitability of available drinking water for safe consumption is considered. It is proposed to use models built by machine learning methods so that when analyzing water samples it is possible to focus on the main parameters so that limited resources are not directed unnecessarily to less important features. To evaluate the effectiveness of the proposed models, test data that were not used to build the models and several different criteria for evaluating the quality of the models were used.
  • Ескіз
    ДокументВідкритий доступ
    Models for analyzing and forecasting share prices on the stock exchange
    (КПІ ім. Ігоря Сікорського, 2024) Piznak, R.; Likhouzova, T.
    The work is devoted to the analysis and forecasting of share prices for four leading technology companies: Nvidia, Apple, Google, and Netflix. These companies are leaders in their fields and have a significant impact on the global economy. The goal is to study the dependencies affecting the share prices of companies, as well as to develop models for forecasting future trends. In the work, a thorough analysis of historical data on company share prices and their macroeconomic indicators was carried out. The study was based on the fundamental concepts of economic science. The study results are expected to provide a deeper understanding of the prospects of these companies.
  • Ескіз
    ДокументВідкритий доступ
    Models for analyzing the complexity of english words in the text on the scale from A1 to C2
    (КПІ ім. Ігоря Сікорського, 2024) Bielikov, M.; Likhouzova, T.; Oliinyk, Y.
    At the current stage of globalization, English plays a key role as the language of international communication. This leads to the fact that more and more people become its carriers at various levels. The work is devoted to the analysis of English words on the scale from A1 to C2, which corresponds to the lowest and highest levels of proficiency according to the CEFR standards. A model that predicts the difficulty of words in a text can be used to improve the educational process. For example, it is possible to find a list of likely unknown and difficult words for the end user in any text depending on his level of English language proficiency. This approach will facilitate the language learning process by providing a personalized list of words to focus on. Also, the model can be useful for analyzing the complexity of texts depending on the number of words of each level of complexity in them. This can help teachers prepare materials that match the level of knowledge of their students, as well as identify words that may be difficult for them to understand. An application in the Python programming language is proposed, which receives a sample of data from the created storage, displays them graphically, performs intellectual analysis, trains and compares models according to accuracy, precision, recall and f1-score metrics. For data analysis and prediction of the level of complexity of English words, the following models were used: PchipInterpolator, logarithmic model, Gradient Boosting, Random Forest and XGB.
  • Ескіз
    ДокументВідкритий доступ
    Models for forecasting flight delays
    (КПІ ім. Ігоря Сікорського, 2023) Tarasonok, D.; Oliinyk, Y.; Likhouzova, T.
    The problem of improving the operation of airports and air carriers is considered. It is proposed to use machine learning models and technologies to predict flight delays. Several different quality measures are used to evaluate the effectiveness of the proposed models, which diversely reflect the expediency of using these models in the context of the needs of each task.
  • Ескіз
    ДокументВідкритий доступ
    Models for forming the market value of a real estate
    (КПІ ім. Ігоря Сікорського, 2022) Konchynskyi, V.; Likhouzova, T.
  • Ескіз
    ДокументВідкритий доступ
    Models for researching prospects for the development of the aviation industry
    (КПІ ім. Ігоря Сікорського, 2024) Tarasonok, D.; Likhouzova, T.
    Abstract: Considered the problem of prospects for the development of the aviation industry in the world. It is proposed to use machine learning models and technologies for clustering countries by the number of air flights and forecasting the production of aircraft in the future. Several different quality measures were used to evaluate the effectiveness of the proposed models, which reflect the needs of each task in various ways.
  • Ескіз
    ДокументВідкритий доступ
    Problems With Effective Traffic Management
    (КПІ ім. Ігоря Сікорського, 2021) Rubel, H.; Likhouzova, T.
  • Ескіз
    ДокументВідкритий доступ
    Software tools for creating interfaces for interaction with Arduino via Bluetooth
    (КПІ ім. Ігоря Сікорського, 2023) Kliuba, M.; Likhouzova, T.
    The problem of communication between microcontrollers of the AVR family and other devices via Bluetooth using special modules is considered. A comprehensive solution is proposed, including a modified interaction protocol, an Arduino library that implements interaction on the microcontroller side, and a mobile application for creating interfaces that allows a user to interact with Arduino via Bluetooth.