The Use of Artificial Neural Networks for Forecasting of Air Temperature inside a Heated Foil Tunnel

Sławomir Francik , Sławomir Kurpaska


It is important to correctly predict the microclimate of a greenhouse for control and crop management purposes. Accurately forecasting temperatures in greenhouses has been a focus of research because internal temperature is one of the most important factors influencing crop growth. Artificial Neural Networks (ANNs) are a powerful tool for making forecasts. The purpose of our research was elaboration of a model that would allow to forecast changes in temperatures inside the heated foil tunnel using ANNs. Experimental research has been carried out in a heated foil tunnel situated on the property of the Agricultural University of Krakow. Obtained results have served as data for ANNs. Conducted research confirmed the usefulness of ANNs as tools for making internal temperature forecasts. From all tested networks, the best is the three-layer Perceptron type network with 10 neurons in the hidden layer. This network has 40 inputs and one output (the forecasted internal temperature). As the networks input previous historical internal temperature, external temperature, sun radiation intensity, wind speed and the hour of making a forecast were used. These ANNs had the lowest Root Mean Square Error (RMSE) value for the testing data set (RMSE value = 3.7 °C).
Author Sławomir Francik (FoPaPE / DoMEaA)
Sławomir Francik,,
- Department of Mechanical Engineering and Agrophysics
, Sławomir Kurpaska (FoPaPE / Department of Bioprocess Engineering, Power Engineering and Automation)
Sławomir Kurpaska,,
- Department of Bioprocess Engineering, Power Engineering and Automation
Journal seriesSensors, [SENSORS-BASEL], ISSN 1424-8220, e-ISSN 1424-3210, (N/A 100 pkt)
Issue year2020
Publication size in sheets0.8
Article number652
Keywords in Englishartificial neural network; perceptron; temperature; forecasting; greenhouse; greenhouse foil tunnel
ASJC Classification1303 Biochemistry; 1602 Analytical Chemistry; 2208 Electrical and Electronic Engineering; 3107 Atomic and Molecular Physics, and Optics
Languageen angielski
LicenseJournal (articles only); author's original; Uznanie Autorstwa (CC-BY); after publication
The Use of Artificial Neural Networks for Forecasting of Air Temperature inside a Heated Foil Tunnel of 14-05-2020
1,09 MB
Score (nominal)100
Score sourcejournalList
Publication indicators WoS Citations = 2; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 1.393; WoS Impact Factor: 2018 = 3.031 (2) - 2018=3.302 (5)
Citation count*
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Finansowanie Article Processing Charges were financed from the subsidy of the Ministry of Science and Higher Education for the Agricultural University of Hugo Kołła˛taj in Krakow for the year 2020.
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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