Vol. 18, No. 8, August 31, 2024
10.3837/tiis.2024.08.021,
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Abstract
As problems such as water pollution and fish species depletion have become serious, a land-based fish farming is receiving a great attention for ensuring stable productivity. In the fish farming, it is important to determine the timing of shipments, as one of key factors to increase net profit on the aquaculture. In this paper, we propose a system for predicting net profit to support decision of timing of shipment using fish farming-related statistical data. The prediction system consists of growth and farm-gate price prediction models, a cost statistics table, and a net profit estimation algorithm. The Gaussian process regression (GPR) model is exploited for weight prediction based on the analysis that represents the characteristics of the weight data of cultured fish under the assumption of Gaussian probability processes. Moreover, the long short-term memory (LSTM) model is applied considering the simple time series characteristics of the farm-gate price data. In the case of GPR model, it allows to cope with data missing problem of the weight data collected from the fish farm in the time and temperature domains. To solve the problem that the data acquired from the fish farm is aperiodic and small in amount, we generate the corresponding data by adopting a data augmentation method based on the Gaussian model. Finally, the estimation method for net profit is proposed by concatenating weight, price, and cost predictions. The performance of the proposed system is analyzed by applying the system to the Korean flounder data.
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Cite this article
[IEEE Style]
J. Lee, W. Jeon, J. Sung, K. Kwon, Y. Kim, K. Park, J. Paik, S. Cho, "Design of an Aquaculture Decision Support Model for Improving Profitability of Land-based Fish Farm Based on Statistical Data," KSII Transactions on Internet and Information Systems, vol. 18, no. 8, pp. 2431-2449, 2024. DOI: 10.3837/tiis.2024.08.021.
[ACM Style]
Jaeho Lee, Wongi Jeon, Juhyoung Sung, Kiwon Kwon, Yangseob Kim, Kyungwon Park, Jongho Paik, and Sungyoon Cho. 2024. Design of an Aquaculture Decision Support Model for Improving Profitability of Land-based Fish Farm Based on Statistical Data. KSII Transactions on Internet and Information Systems, 18, 8, (2024), 2431-2449. DOI: 10.3837/tiis.2024.08.021.
[BibTeX Style]
@article{tiis:101109, title="Design of an Aquaculture Decision Support Model for Improving Profitability of Land-based Fish Farm Based on Statistical Data", author="Jaeho Lee and Wongi Jeon and Juhyoung Sung and Kiwon Kwon and Yangseob Kim and Kyungwon Park and Jongho Paik and Sungyoon Cho and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2024.08.021}, volume={18}, number={8}, year="2024", month={August}, pages={2431-2449}}