Prediction of Paprika Yield Using Multiple Linear Regression 


Vol. 46,  No. 11, pp. 2048-2055, Nov.  2021
10.7840/kics.2021.46.11.2048


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  Abstract

Recently, in agriculture, high crop productivity is a main aim that can be achieved by integrating bigdata and IoT technologies. Diverse methods have been utilized for crop yield prediction or forecasting in digital agriculture. In this paper, we use environment and yield data collected in paprika smart farms. Firstly we build an optimal model relating the environment and yield. Then based on the optimal model, a methodology for yield prediction is presented. In experiment, we achieved R²= [0.9171, 0.9714] that indicates the feasibility of predicted yields. We expect that this result will be utilized in decision making systems.

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  Cite this article

[IEEE Style]

I. Hwang, H. Noh, D. Yang, M. Kim, "Prediction of Paprika Yield Using Multiple Linear Regression," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 11, pp. 2048-2055, 2021. DOI: 10.7840/kics.2021.46.11.2048.

[ACM Style]

In-Chul Hwang, Heesun Noh, Dong-Il Yang, and Manbae Kim. 2021. Prediction of Paprika Yield Using Multiple Linear Regression. The Journal of Korean Institute of Communications and Information Sciences, 46, 11, (2021), 2048-2055. DOI: 10.7840/kics.2021.46.11.2048.

[KICS Style]

In-Chul Hwang, Heesun Noh, Dong-Il Yang, Manbae Kim, "Prediction of Paprika Yield Using Multiple Linear Regression," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 11, pp. 2048-2055, 11. 2021. (https://doi.org/10.7840/kics.2021.46.11.2048)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880