A Study on the Prediction Model of Chicken Price Using a Multi-Variable LSTM Deep Learning Network 


Vol. 47,  No. 12, pp. 2058-2064, Dec.  2022
10.7840/kics.2022.47.12.2058


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  Abstract

The domestic chicken industry is expected to exceed 400 billion won in market size by 2022, and its growth rate is very steep. However, as the operating profit ratio of chicken producers continues to decrease, companies are trying to predict the selling price of chicken to reduce operating losses. In this study attempted to develop a scientific prediction model that introduced artificial intelligence technology beyond the existing statistical approach to predicting broiler prices. Previous studies in the price prediction were analyzed to select and study LSTM(Long Short-Term Memory) that showed high performance in predicting nonlinear time series data. Various time series data related to the formation of the broiler price were collected and analyzed among the data disclosed by the Korea poultry association, the Korea Meteorological Administration, the Korea Animal Health Integrated System, and the Statistics Korea. All of the collected data were refined in the same time unit. The developed multi-variable LSTM model showed about 94.0% accuracy as a result of verification through 10% test data separated from the learning data. The results of this study are also expected to be used in the development of mid- to long-term broiler price prediction models considering the utilization of companies.

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[IEEE Style]

Y. Lee, K. Ko, D. Hwang, S. Lee, J. Cho, "A Study on the Prediction Model of Chicken Price Using a Multi-Variable LSTM Deep Learning Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 12, pp. 2058-2064, 2022. DOI: 10.7840/kics.2022.47.12.2058.

[ACM Style]

Yeo-jin Lee, Kyeong-Seok Ko, Dong-Hyun Hwang, Seul-a Lee, and Ju-phill Cho. 2022. A Study on the Prediction Model of Chicken Price Using a Multi-Variable LSTM Deep Learning Network. The Journal of Korean Institute of Communications and Information Sciences, 47, 12, (2022), 2058-2064. DOI: 10.7840/kics.2022.47.12.2058.

[KICS Style]

Yeo-jin Lee, Kyeong-Seok Ko, Dong-Hyun Hwang, Seul-a Lee, Ju-phill Cho, "A Study on the Prediction Model of Chicken Price Using a Multi-Variable LSTM Deep Learning Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 12, pp. 2058-2064, 12. 2022. (https://doi.org/10.7840/kics.2022.47.12.2058)
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