IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i6p780-d826878.html
   My bibliography  Save this article

Neural Network Model for Greenhouse Microclimate Predictions

Author

Listed:
  • Theodoros Petrakis

    (Department of Agriculture, University of Patras, 26504 Patras, Greece)

  • Angeliki Kavga

    (Department of Agriculture, University of Patras, 26504 Patras, Greece)

  • Vasileios Thomopoulos

    (Computer Engineering and Informatics Department, University of Patras, 26504 Patras, Greece)

  • Athanassios A. Argiriou

    (Laboratory of Atmospheric Physics, Department of Physics, University of Patras, 6500 Patras, Greece)

Abstract

Food production and energy consumption are two important factors when assessing greenhouse systems. The first must respond, both quantitatively and qualitatively, to the needs of the population, whereas the latter must be kept as low as possible. As a result, to properly control these two essential aspects, the appropriate greenhouse environment should be maintained using a computational decision support system (DSS), which will be especially adaptable to changes in the characteristics of the external environment. A multilayer perceptron neural network (MLP-NN) was designed to model the internal temperature and relative humidity of an agricultural greenhouse. The specific NN uses Levenberg–Marquardt backpropagation as a training algorithm; the input variables are the external temperature and relative humidity, wind speed, and solar irradiance, as well as the internal temperature and relative humidity, up to three timesteps before the modeled timestep. The maximum errors of the modeled temperature and relative humidity are 0.877 K and 2.838%, respectively, whereas the coefficients of determination are 0.999 for both parameters. A model with a low maximum error in predictions will enable a DSS to provide the appropriate commands to the greenhouse actuators to maintain the internal conditions at the desired levels for cultivation with the minimum possible energy consumption.

Suggested Citation

  • Theodoros Petrakis & Angeliki Kavga & Vasileios Thomopoulos & Athanassios A. Argiriou, 2022. "Neural Network Model for Greenhouse Microclimate Predictions," Agriculture, MDPI, vol. 12(6), pages 1-17, May.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:6:p:780-:d:826878
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/6/780/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/12/6/780/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yongtao Shen & Ruihua Wei & Lihong Xu, 2018. "Energy Consumption Prediction of a Greenhouse and Optimization of Daily Average Temperature," Energies, MDPI, vol. 11(1), pages 1-17, January.
    2. Angeliki Kavga & Vasileios Thomopoulos & Pantelis Barouchas & Nikolaos Stefanakis & Aglaia Liopa-Tsakalidi, 2021. "Research on Innovative Training on Smart Greenhouse Technologies for Economic and Environmental Sustainability," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    3. Barkat Rabbi & Zhong-Hua Chen & Subbu Sethuvenkatraman, 2019. "Protected Cropping in Warm Climates: A Review of Humidity Control and Cooling Methods," Energies, MDPI, vol. 12(14), pages 1-24, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Piotr Boniecki & Agnieszka Sujak & Gniewko Niedbała & Hanna Piekarska-Boniecka & Agnieszka Wawrzyniak & Andrzej Przybylak, 2023. "Neural Modelling from the Perspective of Selected Statistical Methods on Examples of Agricultural Applications," Agriculture, MDPI, vol. 13(4), pages 1-19, March.
    2. Oladayo S. Ajani & Member Joy Usigbe & Esther Aboyeji & Daniel Dooyum Uyeh & Yushin Ha & Tusan Park & Rammohan Mallipeddi, 2023. "Greenhouse Micro-Climate Prediction Based on Fixed Sensor Placements: A Machine Learning Approach," Mathematics, MDPI, vol. 11(14), pages 1-14, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Premaratne Samaranayake & Chelsea Maier & Sachin Chavan & Weiguang Liang & Zhong-Hua Chen & David T. Tissue & Yi-Chen Lan, 2021. "Energy Minimisation in a Protected Cropping Facility Using Multi-Temperature Acquisition Points and Control of Ventilation Settings," Energies, MDPI, vol. 14(19), pages 1-18, September.
    2. Gianluca Serale & Luca Gnoli & Emanuele Giraudo & Enrico Fabrizio, 2021. "A Supervisory Control Strategy for Improving Energy Efficiency of Artificial Lighting Systems in Greenhouses," Energies, MDPI, vol. 14(1), pages 1-19, January.
    3. Morice R. O. Odhiambo & Adnan Abbas & Xiaochan Wang & Ehsan Elahi, 2020. "Thermo-Environmental Assessment of a Heated Venlo-Type Greenhouse in the Yangtze River Delta Region," Sustainability, MDPI, vol. 12(24), pages 1-34, December.
    4. Premaratne Samaranayake & Weiguang Liang & Zhong-Hua Chen & David Tissue & Yi-Chen Lan, 2020. "Sustainable Protected Cropping: A Case Study of Seasonal Impacts on Greenhouse Energy Consumption during Capsicum Production," Energies, MDPI, vol. 13(17), pages 1-23, August.
    5. Chul-Ho Kim & Seung-Eon Lee & Kang-Soo Kim, 2018. "Analysis of Energy Saving Potential in High-Performance Building Technologies under Korean Climatic Conditions," Energies, MDPI, vol. 11(4), pages 1-34, April.
    6. Gloria Alexandra Ortiz Rocha & Maria Angelica Pichimata & Edwin Villagran, 2021. "Research on the Microclimate of Protected Agriculture Structures Using Numerical Simulation Tools: A Technical and Bibliometric Analysis as a Contribution to the Sustainability of Under-Cover Cropping," Sustainability, MDPI, vol. 13(18), pages 1-40, September.
    7. Chiara Terrosi & Sonia Cacini & Gianluca Burchi & Maurizio Cutini & Massimo Brambilla & Carlo Bisaglia & Daniele Massa & Marco Fedrizzi, 2020. "Evaluation of Compressor Heat Pump for Root Zone Heating as an Alternative Heating Source for Leafy Vegetable Cultivation," Energies, MDPI, vol. 13(3), pages 1-15, February.
    8. Jerónimo Ramos-Teodoro & Adrián Giménez-Miralles & Francisco Rodríguez & Manuel Berenguel, 2020. "A Flexible Tool for Modeling and Optimal Dispatch of Resources in Agri-Energy Hubs," Sustainability, MDPI, vol. 12(21), pages 1-24, October.
    9. Yuying Liu & Kaiyao Shi & Ziqi Liu & Ling Qiu & Yan Wang & Hao Liu & Xinhong Fu, 2022. "The Effect of Technical Training Provided by Agricultural Cooperatives on Farmers’ Adoption of Organic Fertilizers in China: Based on the Mediation Role of Ability and Perception," IJERPH, MDPI, vol. 19(21), pages 1-20, November.
    10. Ralph De Witte & Dirk Janssen & Samir Sayadi Gmada & Carmen García-García, 2023. "Best Practices for Training in Sustainable Greenhouse Horticulture," Sustainability, MDPI, vol. 15(7), pages 1-26, March.
    11. Fahad Awjah Almehmadi & Kevin P. Hallinan & Rydge B. Mulford & Saeed A. Alqaed, 2020. "Technology to Address Food Deserts: Low Energy Corner Store Groceries with Integrated Agriculture Greenhouse," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    12. Lin, Terry & Goldsworthy, Mark & Chavan, Sachin & Liang, Weiguang & Maier, Chelsea & Ghannoum, Oula & Cazzonelli, Christopher I. & Tissue, David T. & Lan, Yi-Chen & Sethuvenkatraman, Subbu & Lin, Han , 2022. "A novel cover material improves cooling energy and fertigation efficiency for glasshouse eggplant production," Energy, Elsevier, vol. 251(C).
    13. Artur Nemś & Magdalena Nemś & Klaudia Świder, 2018. "Analysis of the Possibilities of Using a Heat Pump for Greenhouse Heating in Polish Climatic Conditions—A Case Study," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    14. Edwin Villagran & Rommel Leon & Andrea Rodriguez & Jorge Jaramillo, 2020. "3D Numerical Analysis of the Natural Ventilation Behavior in a Colombian Greenhouse Established in Warm Climate Conditions," Sustainability, MDPI, vol. 12(19), pages 1-27, October.
    15. Adriana Reyes-Lúa & Julian Straus & Vidar T. Skjervold & Goran Durakovic & Tom Ståle Nordtvedt, 2021. "A Novel Concept for Sustainable Food Production Utilizing Low Temperature Industrial Surplus Heat," Sustainability, MDPI, vol. 13(17), pages 1-23, August.
    16. Anna-Maria N. Dimitropoulou & Vasileios Z. Maroulis & Eugenia N. Giannini, 2023. "A Simple and Effective Model for Predicting the Thermal Energy Requirements of Greenhouses in Europe," Energies, MDPI, vol. 16(19), pages 1-27, September.
    17. Rabiu, Anis & Adesanya, Misbaudeen Aderemi & Na, Wook-Ho & Ogunlowo, Qazeem O. & Akpenpuun, Timothy D. & Kim, Hyeon Tae & Lee, Hyun-Woo, 2023. "Thermal performance and energy cost of Korean multispan greenhouse energy-saving screens," Energy, Elsevier, vol. 285(C).
    18. Ioana Marcu & Ana-Maria Drăgulinescu & Cristina Oprea & George Suciu & Cristina Bălăceanu, 2022. "Predictive Analysis and Wine-Grapes Disease Risk Assessment Based on Atmospheric Parameters and Precision Agriculture Platform," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    19. Ioan Aschilean & Gabriel Rasoi & Maria Simona Raboaca & Constantin Filote & Mihai Culcer, 2018. "Design and Concept of an Energy System Based on Renewable Sources for Greenhouse Sustainable Agriculture," Energies, MDPI, vol. 11(5), pages 1-12, May.
    20. Jiaming Guo & Yanhua Liu & Enli Lü, 2019. "Numerical Simulation of Temperature Decrease in Greenhouses with Summer Water-Sprinkling Roof," Energies, MDPI, vol. 12(12), pages 1-15, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:12:y:2022:i:6:p:780-:d:826878. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.