IDEAS home Printed from https://ideas.repec.org/a/wsi/jeapmx/v26y2024i01ns1464333223500205.html
   My bibliography  Save this article

Mutated Leader Optimisation Algorithm-Based Microclimate Modelling on Greenhouse Concerning Flower Plant Growth

Author

Listed:
  • Renuka Vinod Chimankare

    (Department of Artificial Intelligence & Data Science, Mumbai University, Navi Mumbai, Maharashtra 400706, India)

  • Subra Das

    (Solar Thermal Engineering, Faculty of Science Engineering and Technology, Amity University Gurgaon, Haryana 122413, India)

  • Karmjeet Kaur

    (Electronics and Communication Engineering, Faculty of Science Engineering and Technology, Amity University Gurgaon, Haryana 122413, India)

  • Dhiraj B. Magare

    (DY Patil Deemed to be University, Navi Mumbai, Maharashtra 400706, India)

Abstract

Microclimate modelling in a greenhouse is complicated due to the model’s irregularity and uncertainty of variable parameters. Evaluating the greenhouse’s changing climate is challenging since the conditions are always changing. As a result, it is necessary to determine the best way to manage the microclimate for the healthy development of growing plants. In order to maximise the growth of blooming plants, a modified leader optimisation algorithm (MLA) is created in this study to control the inside environment of a greenhouse. The implementation is done using greenhouses with a double-span structure located in Punjab and Mohali in India. The recommended approach analyses a number of characteristics, including carbon dioxide (CO2) concentration, temperature, and humidity, to keep track of the greenhouse’s environment. The humidity, temperature and CO2 content of flowering plants are studied using the proposed method implemented using MATLAB tool. The evaluated parameters are compared to conventional techniques like Battle Royale Optimisation (BRO), Particle Swarm Optimisation Algorithm (PSO), and BAT algorithm (BAT). Cost and energy consumption are also calculated for both proposed and existing models. Additionally, for the microclimatic parameters, error metrics, including Mean Absolute Error (MAE), Maximum Absolute Error (MaxAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Standard Deviation (STD) are analysed and compared with the conventional approaches. The comparative outcomes highlight the minimal error metrics of a suggested MLA for temperature, humidity, and CO2 levels in blooming plants. The result analysis proves that the proposed MLA model is better than the previous models for predicting the proper range of CO2 concentration, suitable temperature, and perfect humidity for flowering plants. This demonstrates the effectiveness of the proposed MLA approach compared to the established methods for developing blooming plants.

Suggested Citation

  • Renuka Vinod Chimankare & Subra Das & Karmjeet Kaur & Dhiraj B. Magare, 2024. "Mutated Leader Optimisation Algorithm-Based Microclimate Modelling on Greenhouse Concerning Flower Plant Growth," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 26(01), pages 1-43, March.
  • Handle: RePEc:wsi:jeapmx:v:26:y:2024:i:01:n:s1464333223500205
    DOI: 10.1142/S1464333223500205
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S1464333223500205
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S1464333223500205?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:wsi:jeapmx:v:26:y:2024:i:01:n:s1464333223500205. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/jeapm/jeapm.shtml .

    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.