Кафедра "Комп'ютерна інженерія та програмування"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/1095

Офіційний сайт кафедри https://web.kpi.kharkov.ua/cep

Від 26 листопада 2021 року кафедра має назву – "Комп’ютерна інженерія та програмування"; попередні назви – “Обчислювальна техніка та програмування”, “Електронні обчислювальні машини”, первісна назва – кафедра “Математичні та лічильно-вирішальні прилади та пристрої”.

Кафедра “Математичні та лічильно-вирішальні прилади та пристрої” заснована 1 вересня 1961 року. Організатором та її першим завідувачем був професор Віктор Георгійович Васильєв.

Кафедра входить до складу Навчально-наукового інституту комп'ютерних наук та інформаційних технологій Національного технічного університету "Харківський політехнічний інститут". Перший випуск – 24 інженери, підготовлених кафедрою, відбувся в 1964 році. З тих пір кафедрою підготовлено понад 4 тисячі фахівців, зокрема близько 500 для 50 країн світу.

У складі науково-педагогічного колективу кафедри працюють: 11 докторів технічних наук, 21 кандидат технічних наук, 1 – економічних, 1 – фізико-математичних, 1 – педагогічних, 1 доктор філософії; 9 співробітників мають звання професора, 14 – доцента, 2 – старшого наукового співробітника.

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2018 - 20192

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Автор: search.filters.author.Kalimulin, T.Містить файли: Так

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  • Ескіз
    Документ
    Prognosis method of unfavorable airborne events during flight based on convolutional and recurrent neural networks
    (Національний технічний університет "Харківський політехнічний інститут", 2019) Gryshmanov, E.; Kalimulin, T.; Zakharchenko, I.
    This paper contains formal problem definition of predicting unfavorable airborne events during flight. Restrictions and assumptions are put into the prognosis method of unfavorable airborne events during flight. Mathematical apparatus used to build prognosis method is suggested. As a basic mathematical apparatus it is suggested to use, recurrent neural networks (RNN) basedon LSTM modules and convolutional neural networks (CNN). Analysis of these neural networks has shown that RNN based on LSTM modules are mostly effective when analyzing structured text, such as report of investigation of airborne accidents. In its turn, CNN are effective when analyzing unstructured text, such as text messages about the flight situation based on the information from external sources. Prognosis method of unfavorable airborne events during flightbased on convolutional and recurrent neural networks is developed. In case of solving the task of prediction of unfavorable airborne events during flight RNN are used for initial setup of the Embedding layer of the structured training data in the process of hybrid neural network training. CNN are used during the direct operation of hybrid neural network model of prediction of unfavorable airborne events during flight.
  • Ескіз
    Документ
    Imitation model of support for decision-making based on assessment of the situation by operators of the automated air traffic control system
    (Національний технічний університет "Харківський політехнічний інститут", 2018) Dmitriiev, O.; Borozenec, I.; Shilo, S.; Kalimulin, T.
    A human-operator cannot conduct a situation assessment in a timely manner and to react in a proper manner when situation changes. The problem is worsening with the uncertain procedure of selection of dispatchers for duty shifts in control centers and their adequate preparation to carry out the tasks for intended purpose. This doesn’t allow to reach the adequate level of competency during the process of their professional activities. Aim of the article. Developing an imitation model of the operator's complex activities to make a decision based on the situation assessment. The results of thework. The analysis of automated air traffic control system (AATCS) operator activities while assessing the situation with use of existing automation complexes allowed to identify following limitations of informational support of AATCS, which are influencing the effectiveness of its work. Most of the time of situation assessment (up to 41%) is spent by operator to receive additional information from another decision makers and informational elements, showed as part of informational model (IM). These time expenditures are due to low level of information content of information elements presented as part of IM and which are not corresponding to the character of the operator's activity in situation assessment. Methods for reducing the errors of the ACS operator can be divided into the following groups: automation of the most complex operations; introduction of information redundancy at the stage of designing systems for ensuring operators activities; increasing the workload of operators; advanced training for the operator; increased responsibility for errors with increasing interest in error - free operation etc. The generalized analysis of the operator's activity is conducted, the features of the operator's work with the information model are marked; the directions of the conceptual model formation in the decision-making process during the situation assessment are determined; simulation modeling has been carried out and a model of the operator's activity has been developed for the study of the activities of decision-makers during the situation assessment; giving the estimation of time expenses for performance of the various actions connected with the analysis of information models in various conditions.