Study of the Optimization Control of Agricultural Greenhouse Climatic Parameters by the Integration of Machine Learning-Reference-Cited by-同舟云学术

Study of the Optimization Control of Agricultural Greenhouse Climatic Parameters by the Integration of Machine Learning

Published:2023 Issue: Volume: Page:334-346
ISSN:2367-3370
Container-title:Artificial Intelligence and Industrial Applications
language:
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Author:

Boudnaya Jaouad,Huynh Nina Aslhey,Gomgnimbou Ouèdan Jhonn,Aya Kechchour,Yassir Ait Omar,Mkhida Abdelhak

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-43520-1_28

Reference13 articles.

1. Guo, A., et al.: Modeling and optimization of environment in agricultural greenhouses for improving cleaner and sustainable crop production. J. Cleaner Prod. 285, p.124843 (2020)

2. Boodi, A., et al.: Intelligent systems for building energy and occupant comfort optimization: a state of the art review and recommendations. Energies 11(10), 2604 (2018)

3. Ghani, S., et al.: Design challenges of agricultural greenhouses in hot and arid environments–a review. Eng. Agriculture, Environ. Food 12(1), 48–70 (2019)

4. Hamidane, H., et al.: Application analysis of ANFIS strategy for greenhouse climate parameters prediction: internal temperature and internal relative humidity case of study. The 4th International Conference of Computer Science and Renewable Energies, (ICCSRE’2021), 297 (2021)

5. Prakash, O., et al.: ANFIS prediction model of a modified active greenhouse dryer in no-load conditions in the month of january. International Journal of Advanced Computer Research, Volume-3 Number-1 Issue-8 (2013)

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