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Journal Article
지도학습 기반 수출물량 및 수출금액 예측 모델 개발
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- Issue Date
- 2023-06
- Citation
- 한국산업경영시스템학회지, v.46, no.2, pp.152-159
- ISSN
- 2005-0461
- Publisher
- 한국산업경영시스템학회
- Language
- Korean
- Type
- Journal Article
- Abstract
- Due to COVID-19, changes in consumption trends are taking place in the distribution sector, such as an increase in non-face-to-face consumption and a rapid growth in the online shopping market. However, it is difficult for small and medium-sized export sellers to obtain forecast information on the export market by country, compared to large distributors who can easily build a global sales network.This study is about the prediction of export amount and export volume by country and item for market information analysisof small and medium export sellers. A prediction model was developed using Lasso, XGBoost, and MLP models based on supervised learning and deep learning, and export trends for clothing, cosmetics, and household electronic devices were predicted for Korea's major export countries, the United States, China, and Vietnam. As a result of the prediction, the performance of MAE and RMSE for the Lasso model was excellent, and based on the development results, a market analysis system for small and medium sellers was developed.
- KSP Keywords
- Consumption trends, Face-to-face, Market analysis, Online shopping, Supervised Learning, United States, analysis system, deep learning(DL), electronic devices, export volume, market information