| Номер документа в системі: | 356001 |
| Автор: | Dovbysh A. S., Velykodnyi D. V., Protsenko O. B., Zimovets V. I. |
| Назва документа: | Optimization of parameters of machine learning of the system of functional diagnostics of the electric drive of a shaft lifting machine = Оптимізація параметрів машинного навчання системи функціонального діагностування електроприводу шахтної підйомно |
| УДК | 681.518+004.93+621.86/.87 |
| Мова документу | Англійська |
| Аннотація | Relevance. The actual task of increasing the functional efficiency of machine learning of the system of functional diagnosis of the electric drive of a hoisting mine machine is solved.
The specific objective of this study was to develop a method for the information synthesis of a learning system for the functional diagnosis of the electric drive of a hoisting mine machine, which allows increasing the reliability and efficiency of diagnostic solutions in accordance with the decisive rules built in the process of machine learning.
Method. The method of information-extreme machine learning of the system of functional diagnosis of the electric drive of a mine-hoisting machine is proposed, based on the maximization of the information capacity of the system in the process of its training. Based on the computer-generated optimal learning parameters of the hyperspherical containers of the recognition classes, within the framework of the geometric approach, decisive rules that are practically invariant to th |
| Кількість сторінок | P. 44-50. |