A Comparative Study on Machine Learning Models for Paprika Growth Prediction Model with Temperature Changes 


Vol. 46,  No. 12, pp. 2393-2402, Dec.  2021
10.7840/kics.2021.46.12.2393


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  Abstract

Since temperature changes of smart farms are factors which are closely related with crop growth, production, insect infestation, and management efficiency, the appropriate response against the changes is important. To use energy efficiently and control the temperature optimally, smart technologies like renewable energy, data analysis and machine learning need to be actively applied in greenhouses. Machine learning with data analysis is a powerful model that can predict the future with existing data, and has recently been used in various fields. This paper proposes an optimal energy utilization prediction model using machine learning for crop growth with temperature changes in smart farms. The proposed study proposes an optimal model through prediction efficiency experiments using machine learning models such as support vector machine, random forest, eXtreme Gradient Boosting, and gradient boosting machine. As a result, SVM and GBM-based models showed prediction performance better than RF-based models. SVM and GBM-based models showed better predictive performance compared to RF-based models. In particular, the GBM-based model is more useful than other models in predicting temperature changes according to energy consumption. The proposed model can be used to develop various service applications for temperature and energy control for crop growth in smart farms.

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  Cite this article

[IEEE Style]

S. Venkatesan, J. Lim, C. Shin, Y. Cho, "A Comparative Study on Machine Learning Models for Paprika Growth Prediction Model with Temperature Changes," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 12, pp. 2393-2402, 2021. DOI: 10.7840/kics.2021.46.12.2393.

[ACM Style]

SaravanaKumar Venkatesan, Jonghyun Lim, Chanagsun Shin, and Yongyun Cho. 2021. A Comparative Study on Machine Learning Models for Paprika Growth Prediction Model with Temperature Changes. The Journal of Korean Institute of Communications and Information Sciences, 46, 12, (2021), 2393-2402. DOI: 10.7840/kics.2021.46.12.2393.

[KICS Style]

SaravanaKumar Venkatesan, Jonghyun Lim, Chanagsun Shin, Yongyun Cho, "A Comparative Study on Machine Learning Models for Paprika Growth Prediction Model with Temperature Changes," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 12, pp. 2393-2402, 12. 2021. (https://doi.org/10.7840/kics.2021.46.12.2393)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880