AUTOMATED CONTROL SYSTEM IN GREENHOUSE WITH NEURAL NETWORK PREDICTIONS OF EXTERNAL DISTURBANCES

Authors

  • A. Dudnyk

Abstract

Efficiency of creation automation control system in a greenhouse with using solar radiation intensity and temperature predictions by neural networks is shown.

References

Lysenko V., Shtepa V., Dudnyk A. 2011: Probabilistic (Bayesian) neural network of temperature pattern classification. Journal of Agricultural Science. 4, 53 – 56.

Lysenko V., Dudnyk A. 2011: Optimal control: status and prospects in the Greenhouse industry. Scientific Herald of National University of Life and Environmental Sciences of Ukraine. 166, 104 – 113.

Lysenko V., Shtepa V., Zayets N., Dudnyk A. 2011: Neural network forecasting of outside temperature time series. Biological Resources and Nature Management. 3 - 4, 102 – 108.

Lysenko V., Shtepa V., Dudnyk A. 2012: The Hilbert-Huang transform and the filtration the time series of solar radiation. Herald of Kharkov Petro Vasylenko National Technical University of Agriculture. 130, 55 – 57.

Huang N. E. Shen Z., Long S. R., Wu M. C., Shih H. H., Zheng Q., Yen N.-C., Tung С. C., and Liu H. H. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of R. Soc. London, Ser. A, 454, 903 – 995, 1998

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No. 1 (2015): (укр)

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Статті

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