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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  • Ескіз
    Публікація
    Застосування нечітких множин типу-2 при проєктуванні бортової комп'ютерної системи
    (ФОП Тарасенко В. П., 2021) Заковоротний, Олександр Юрійович; Харченко, А. О.
  • Ескіз
    Документ
    Construction of information technology for development of knowledge base on identification of urban structures on digital space and aerial photographs in the urban environment monitoring
    (Національний технічний університет "Харківський політехнічний інститут", 2020) Pustovarov, Volodymyr Volodymyrovich
    The efficiency and quality of modern city management are directly linked to the relevant monitoring. Improving the efficiency and validity of the obtained data on the urban environment is possible due to the automation of the system of urban objects identification on digital space and aerial photographs, which involves determining their changes. Therefore, a knowledge base (data), which consists of a set of rules, facts, an inference mechanism that can be implemented through the use of deep neural network or hybrid (fuzzy neural network) models, is therefore needed. This academic paper proposes the technology of formal presentation of the information technology construction for the development of a knowledge base on the identification of urban structures on digital space and aerial photographs in automated monitoring of the urban environment. The developed technology identifies an interdependentset of phases, with the possibility of further parallelization of sub-stages, taking into account the peculiarities of knowledge representation (formalization) on the identification of urban structures on digital space and aerial photographs in automated monitoring of the urban environment.
  • Ескіз
    Документ
    Method of software verification of air objects classification fuzzy logical system
    (Національний технічний університет "Харківський політехнічний інститут", 2018) Timochko, O.
    Objects of different classes are detected in the process of monitoring airspace. The classification of an air object is the process of establishing its belonging to a preassigned class. Classes are automatically determined or set automated. The unambiguous assignment of air objects to a particular class is an actual scientific task. The purpose of the article is to develop a method for verifying software for a fuzzy logical system for classifying air objects. This problemis solved in a fuzzy setting. To solve this problem, an appropriate software verification method has been developed. The method is based on fuzzy colored Petri nets and uses a base of fuzzy productional rules. The structure of the fuzzy network verification model has been developed. The basis of the model is a fuzzy colored Petri net for representing the base of fuzzy production rules for classifying air objects. For the convenience of visualization of the fuzzy network verification model, the interpretation of the elements of the fuzzy colored Petri net is introduced. The analysis of the state space of a fuzzy network verification model reflects all possible markings.The state space allows to obtain the values of the indicators of all the basic properties of the Petri net. The CPN Tools modeling system is used to build and analyze the state space. The full standard report for the fuzzy logical classification system of air objects was obtained from the simulation results. The report fragment with conclusions about the correctness of the model is given. The report contains sections of state space statistics - the number of nodes, arcs and status, indicators of the properties of reversibility, limitation, survivability and fairness of transitions. The method includes five steps. 1. A base of fuzzy production rules is being developed. 2. The set of interpretation rules transforms the base of fuzzy production rules into the form of fuzzy colored Petri nets. 3. The model is examined for proper functioning. 4. When an error is detected, its type is analyzed. After its correction, the program repeats, starting with any of stages 1, 2 or 3. 5. Reports on the total space of states with various combinations of source data are issued. A final report is issued after analyzing the correctness of the set of reports and correcting errors that have occurred.
  • Ескіз
    Документ
    Logical-probabilistic representation of causal dependencies between events in business process management
    (Національний технічний університет "Харківський політехнічний інститут", 2018) Chala, O.
    The subject matter of the article are the processes of identifying knowledge in the form of causal relationships based on the analysis of the log of the business process. The goalis to develop a logical-probabilistic model of cause-effect relationships between pairs of log events that describes the implementation of the business process's action to support the solution of the task of automating the construction of the knowledge base of the process management system. Tasks: Select context constraints and limitations on the execution of business process actions that can be obtained as a result of log analysis; develop an approach to extract the probabilistic and logical components of cause-effect dependencies; to develop a logical-probabilistic model of causal relationships. The methodsused are: methods for constructing predicate models; Bayesian methods of constructing probabilistic models. The following results are obtained. Formalized class of causal dependencies for knowledge-intensive business processes. Such dependencies can take into account informal knowledge of the business process. Within this class there are: a predicate description of the state of the context based on information about values of attributes of log events; contextual constraints on doing business process actions; probabilistic conditions for implementing the business process. The scientific novelty of the results obtained is as follows: a logical-probabilistic model of cause-effect relationships between pairs of log events describing the performance of the business process is proposed. The model binds a logical description of the state of the context before and after the completion of each activity of the business process, as well as a logical description of the constraints on the actions of the process and a probabilistic description of the conditions for the execution of these actions. In practical terms, the model provides an opportunity to solve problems of extracting, expandingand integrating knowledge based on the analysis of logs of business processes.