Analysis of a Dataset for Modeling a Transport Conveyor
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Дата
2022
Автори
DOI
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
Анотація
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.
Опис
Ключові слова
transport conveyor, neural network, non-stationary stochastic process, dataset generator
Бібліографічний опис
Pihnastyi O. Analysis of a Dataset for Modeling a Transport Conveyor / O. Pihnastyi, A. Burduk // CEUR Workshop Proceedings. – 2022. – Vol. 3309. – Information Technologies: Theoretical and Applied Problems (ITTAP 2022) : proc. of the 2st Intern. Workshop,Ternopil, Ukraine, November 22-24, 2022 / ed.: Ia. Lytvynenko, S. Lupenko ; Ternopil Ivan Puluj Nation. Technic. Univ. – Electronic text data. – Ternopil, 2022. – P. 319-328. – URL: https://ceur-ws.org/Vol-3309/paper20.pdf, free (accessed 30.01.2023).