• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.128-130
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• 2021

This study aims to implement a Regression Analysis system for predicting the appropriate production of flatfish. Due to Korea's signing of FTAs with countries around the world and accelerating market opening, Korean flatfish farming businesses are experiencing many difficulties due to the specificity and uncertainty of the environment. In addition, there is a need for a solution to problems such as sluggish consumption and price drop due to the recent surge in imported seafood such as salmon and yellowtail and changes in people's dietary habits. in this study, Using the python module, xlwings, it was used to obtain for the production amount of flatfish and to predict the amount of flatfish to be produced later. was used to predict the amount of flatfish to be produced in the future. Therefore, based on the analysis results of this prediction of flatfish production, the flatfish aquaculture industry will be able to come up with a plan to achieve an appropriate production volume and control supply and demand, which will reduce unnecessary economic loss and promote new value creation based on data. In addition, through the data approach attempted in this study, various analysis techniques such as artificial neural networks and multiple regression analysis can be used in future research in various fields, which will become the foundation of basic data that can effectively analyze and utilize big data in various industries.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.321-324
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• 2022

The Korean halibut farming industry suffer from price instability and demand decrease due to various environmental and social issues. It is urgent to predict the appropriate amount of halibut production. However, it is not easy for employments working in the halibut farming industry to handle statistical tools in order to perform the prediction. In this paper, we implemented a Excel-based regression analysis tool that allows users to get a regression analysis result by just entering historical data in a sheet. Our tool will reduce workloads of employments working in the halibut farming industry by enabling them to perform a regression analysis with Excel on-the-fly. This study expect that by using the tool the halibut farming industry cope actively with the real-time change in the industry.