Abstract
The problem of forecasting the qualitative indicators of onion harvesters was solved using the methodologies of the system analysis and synthesis, physical modeling, based on the theory of artificial neural networks. Analysis of the mathematical model of the working process of onion harvesting machine showed that the increase in the quality indicators of onion harvesting can be ensured by the optimal ratio of internal unregulated parameters of separate executive devices. A change in the process parameters of mechanical means for onion harvesting within design limits does not ensure keeping to agrotechnical requirements. This neural network model for the assessment of quality indicators of functioning elements of the machine for harvesting onion set allows to predict the quality performance indicators on the basis of a large number of external impacts X, affecting the harvesting process. The theory of artificial neural networks allows to describe the technological working process of the machine for harvesting onion set, its individual functioning elements, to predict and evaluate the quality performance indicators both of separate executive devices and the entire machine.
Highlights
The problem of forecasting the qualitative indicators of onion harvesters was solved using the methodologies of the system analysis and synthesis, physical modeling, based on the theory of artificial neural networks
Analysis of the mathematical model of the working process of onion harvesting machine showed that the increase in the quality indicators of onion harvesting can be ensured by the optimal ratio of internal unregulated parameters of separate executive devices
A change in the process parameters of mechanical means for onion harvesting within design limits does not ensure keeping to agrotechnical requirements
Summary
The problem of forecasting the qualitative indicators of onion harvesters was solved using the methodologies of the system analysis and synthesis, physical modeling, based on the theory of artificial neural networks. Модель оценки качественных показателей работы функционирующих элементов машины для уборки лука на основе теории искусственных нейронных сетей позволяет прогнозировать качественные показатели работы на основании большого числа внешних воздействий , оказывающих определяющее влияние на процесс уборки.
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