Кафедра "Інтернет речей"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/5398

Увага! Поповнення колекції кафедри "Інтернет речей" – призупинено.

Від вересня 2022 року кафедри "Інтернет речей" та "Мультимедійних інформаційних технологій і систем" об’єднані у кафедру "Мультимедійні та інтернет технології і системи".

Первісна назва кафедри – "Розподілені інформаційні системи і хмарні технології".

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On constructing a random values generator of the input material flow for transport conveyor models based on neural network
(Видавничий дім "Гельветика", 2024) Pihnastyi, O. M.; Sobol, Maksym
This study examines a method for constructing a generator of random values of the input material flow to form a training data set for highly efficient transport conveyor models based on a neural network. A comparative analysis of the experimental, approximated and generated realizations for the input material flow of the conveyor type transport system is presented.
Predictive analysis of the interval material flow rates in transport conveyors based on experimental data
(2024) Pihnastyi, O. M.; Sobol, Maksym; Burduk, Anna
This study examines a method for constructing a generator of random values of the input flow of material to form a training data set in highly efficient transport conveyor models based on a neural network. Dimensionless parameters are introduced that make it possible to represent the model of the input material flow of a transport conveyor in a dimensionless form. Coordinate functions are determined to approximate the experimental realization of the input material flow. A canonical decomposition of the experimental realization of the input material flow in terms of coordinate functions based on the use of fixed intervals is presented. For the selected canonical decomposition of the experimental realization of the input material flow, a theoretical correlation function is determined. It is shown that as the number of intervals increases, the correlation function of the experimental realization tends to the theoretical correlation function. The stages of constructing a random value generator for the input material flow are presented in detail. A comparative analysis of the experimental, approximated and generated realization for the input material flow is presented and estimates of the statistical characteristics of the realizations of the input material flow are given. The correlation functions constructed for the experimental, approximated and generated realizations of the input material flow are analyzed. An estimate is given of the length of the time interval required to carry out experimental changes in the input material flow.
Математична модель масообміну каталітичного процесу конверсії випускних газів двигунів внутрішнього згоряння
(Національний технічний університет "Харківський політехнічний інститут", 2010) Ведь, Олена Валеріївна; Толчинський, Ю. А.
Математическое моделирование в страховании жизни
(Національний технічний університет "Харківський політехнічний інститут", 2015) Тубичко, К. В.; Ведь, Олена Валеріївна
Logical Networks and Their Usage in Solving of Morphological Tasks
(2020) Shubin, Igor; Kozyriev, Andrii; Pitiukova, Mariia; Svyatkin, Yaroslav
In the study of category theory, along with the usual concept of category met. As a result of developing a link between two different definitions of a category and a more general notion of an objectless category, it was found out that a whole class of isomorphic categories with objects corresponds to it. A universal mathematical apparatus of the algebra of predicates was proposed, and more precisely its central fragment, which refers to the description of logical spaces – logical analysis. As a result, the interpretation of the category in terms of the algebra of predicates was found – the predicate category Pred, and for both cases: the category with objects and the objectless category.
Analysis of the input material flow of the transport conveyor
(Національний гірничий університет, 2023) Pihnastyi, O. M.; Sobol, Maksym
Purpose. To develop a method for analyzing the material flw entering the input of a conveyor section, based on the decomposition of the input material flw into a deterministic material flw and a stochastic material flw. Methodology. The analysis of experimental data characterizing the input material flw was performed using the methods of the canonical Fourier representation of a random process. Findings. A method for representing a stochastic material flw as a combination of a deterministic process and a stationary random process with ergodic properties is proposed. Originality. The originality of the obtained results lies in the fact that, for the fist time, a method of analysis based on the decomposition of the input material flw for a conveyor section has been proposed, which, unlike the existing methods of input flw typing for the mining industry, will allow us to independently perform deterministic flw typing and stochastic material flw typing in transport conveyors. The proposed approach makes it possible to highlight special characteristics separately for deterministic and stochastic material flws. This will make it possible to use the obtained regularities to increase the accuracy of the conveyor model and will accordingly increase the quality of the belt speed control systems and the flw of material coming from the input bunker. The obtained results are of particular importance due to the fact that the characteristics of the deterministic material flw are directly related to the technical or technological factors of material extraction. Practical value. The obtained results allow determining statistically stable regularities for the incoming flw, which makes it possible, based on these regularities from the set of available control algorithms, to choose the optimal control algorithm for the parameters of the operating conveyor section. This allows reducing the enterprise’s energy costs of the transportation of material. The proposed method can be successfully applied to build random number generators simulating the sequence of values of the input flw of material. The developed generators can be used both for validating existing belt speed control systems and creating new control systems based on neural networks. This opens perspectives for the design of effctive systems for controlling the flw parameters of transport system, based on the transport conveyor model, which takes into account the stochastic nature of the incoming material flw.
Методичні вказівки і завдання для організації самостійної роботи студентів з курсу "Теорія ймовірностей"
(Національний технічний університет "Харківський політехнічний інститут", 2022) Іванчихін, Юрій Володимирович; Карпенко, Вячеслав Васильович
Ціль навчальної дисципліни «Теорія ймовірностей» полягає в тому, щоб студент засвоїв математичні методи, які дають можливість аналізувати і моделювати пристрої, процеси і явища, з якими він зустрінеться в майбутньої діяльності як спеціаліст IT галузі, системне ознайомлення студентів з відповідним математичним апаратом теорії ймовірностей, демонстрація можливостей застосування його до розв’язання конкретних прикладних задач комп’ютерної інженерії та інтернету речей, підготовка спеціалістів, що володіють сучасними інформаційними технологіями, використовують моделі штучного інтелекту, створюють програмне забезпечення в умовах невизначеності. Мета самостійної роботи полягає в закріпленні теоретичних знань, одержаних студентами під час вивчення дисципліни «Теорія ймовірностей», їх застосуванні для вирішення конкретних практичних завдань. Виконання індивідуальних завдань сприяє формуванню самостійності в аналізі проведених обчислень, дослідженні практичних задач, які є необхідною складовою підвищення технічного та наукового рівня підготовки студента для вивчення фахових дисциплін, подальшого вміння використовувати отримані знання для реальних задач в галузі комп’ютерної інженерії та інтернету речей. Методичні вказівки до самостіїної роботи студентів з курсу дисципліни «Теорія ймовірностей» містять загальний інформативний блок теоретичного матеріалу, зразки розв’язування задач, методичні рекомендації до вивчення курсу та рішення завдань, варінти практичних завданнь для самостійної індивідуальної роботи, методичні поради щодо їх виконання, питання для самоконтролю та самоперевірки з усіх тем курсу. Для більш фундаментального оволодіння необхідними навичками з курсу теорії ймовірностей рекомендується ознайомлення з літературою, список якої надається.
The Input Material Flow Model of the Transport Conveyor
(Institute of Electrical and Electronics Engineers, Inc., 2022) Pihnastyi, O. M.; Sobol, Maksym
This paper discusses the problem of forming a data set for training a neural network used to build a model of a multi-section conveyor. The analysis of the models, which are used by designing the flow parameters control system of the transport system, is given. The conditions of applying a neural network in the transport conveyer model are justified and determined. Methods for generating a data set for training a neural network are discussed. As the main approach, the use of production data obtained from functioning transport conveyors is considered. Statistically processed data can be used to build generators of stochastic processes that model the incoming material flow for the transport system. The development of these generators to form the input flow of the material of the transport system opens up the possibility of analyzing and monitoring conveyor models in various modes of its configuration. A statistical analysis of the incoming material flow of the transport system was carried out and its number characteristics were determined. The correlation function characterizing the input flow of material for the transport system is considered. The introduction of dimensionless parameters to describe the input material flow made it possible to scale the results of work for a wide class of conveyor-type transport systems.
Analysis of a Dataset for Modeling a Transport Conveyor
(2022) Pihnastyi, O. M.; Burduk, Anna
The analysis of the works, which considered the use of neural networks for modeling a multi-section transport conveyor, was carried out. The prospects for the use of neural networks for the design of highly efficient control systems for the flow parameters of a multi-section transport conveyor are studied. The problem that limits the use of neural networks for building control systems for the flow parameters of a multi-section transport conveyor is considered. The possibility of constructing generators for generating a data set for the process of training a neural network is being studied. A method for generating a data set based on experimentally obtained measurements of the instantaneous values of the input material flow as a result of the operation of industrial transport systems is proposed. Using dimensionless variables, a statistical analysis of a stochastic flow of material entering the input of the transport system was performed. An estimate of the correlation time of a stochastic process characterizing the input flow of material is given. The recommendations on choosing the type of correlation function for the model of the input material flow were confirmed. It is demonstrated that the input flow of material is a non-stationary stochastic process. Approximations for modeling the input flow of materials of the operating transport system are considered.
Use of analytical model for synthesis of algorithms for control of transport conveyor parameters
(Khmelnytskyi national university, 2022) Pihnastyi, O. M.; Sobol, Maksym
This study presents a methodology for synthesizing optimal control algorithms for the flow parameters of a conveyor-type transport system with a variable transport delay. A multi-section transport conveyor is a complex dynamic system with a variable transport delay. The transport conveyor is an important element of the production system, used to synchronize technological operations and move material. The Analytical PiKh-model of the conveyor section was used as a model for designing a control system for flow parameters. The characteristic dimensionless parameters of the conveyor section are introduced and the similarity criteria for the conveyor sections are determined. The model of a conveyor section in a dimensionless form is used to develop a methodology for synthesizing algorithms for optimal control of the flow parameters of a transport conveyor section. The dependencies between the value of the input and output material flow of the section are determined, taking into account the initial distribution of the material along the conveyor section, variable transport delay, restrictions on the specific density of the material, and restrictions on the speed of the belt. The dependencies between the value of the input and output material flow for the case of a constant transport delay are analyzed. A technique for synthesizing algorithms for optimal belt speed control based on the PiKh-model of a conveyor section is presented. As a simplification, a two-stage belt speed control is considered. Particular attention is paid to the methodology for synthesizing optimal control algorithms based on the energy management methodology (TOU-Tariffs). The criteria of control quality are introduced and problems of optimal control of flow parameters of the transport system are formulated. Taking into account differential connections and restrictions on phase variables and admissible controls, which are typical for the conveyor section, the Pontryagin function and the adjoint system of equations are written. As examples demonstrating the design of optimal control, algorithms for optimal control of the flow parameters of the transport system are synthesized and analysis of optimal controls is performed.