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Estimation of the Temperatures in an Experimental Infrared Heated Greenhouse Using Neural Network Models

Estimation of the Temperatures in an Experimental Infrared Heated Greenhouse Using Neural Network Models

Angeliki Kavga, Vassilis Kappatos
Copyright: © 2013 |Volume: 4 |Issue: 2 |Pages: 9
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781466634527|DOI: 10.4018/jaeis.2013040102
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MLA

Kavga, Angeliki, and Vassilis Kappatos. "Estimation of the Temperatures in an Experimental Infrared Heated Greenhouse Using Neural Network Models." IJAEIS vol.4, no.2 2013: pp.14-22. http://doi.org/10.4018/jaeis.2013040102

APA

Kavga, A. & Kappatos, V. (2013). Estimation of the Temperatures in an Experimental Infrared Heated Greenhouse Using Neural Network Models. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 4(2), 14-22. http://doi.org/10.4018/jaeis.2013040102

Chicago

Kavga, Angeliki, and Vassilis Kappatos. "Estimation of the Temperatures in an Experimental Infrared Heated Greenhouse Using Neural Network Models," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 4, no.2: 14-22. http://doi.org/10.4018/jaeis.2013040102

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Abstract

A high quality greenhouse control demands continuous measurements of indoor and outdoor greenhouse conditions. In this work, neural network models were used for reducing the cost and the time of temperature measurements, estimating two of the most important parameters in the operation of the greenhouse, namely the inside air temperature and the cover temperature of greenhouse. An extensive experimental investigation was carried out in an infrared heated greenhouse, using the experimental data to train and validate the neural network models. The modelling results show that the estimated temperatures have been in good agreement with the experimental data with accuracy ranging from 95.64% to 97.67%.

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