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Auxiliary system for prediction of trade volume using tomato big data and data mining methodology
- Issue Date
- Sep-2020
- Publisher
- Pushpa Publishing House
- Keywords
- Agricultural products processing center; Data mining; Regression; Tomato big data; Trade volume prediction
- Citation
- JP Journal of Heat and Mass Transfer, v.2020, no.Special Issue, pp 19 - 30
- Pages
- 12
- Indexed
- SCOPUS
- Journal Title
- JP Journal of Heat and Mass Transfer
- Volume
- 2020
- Number
- Special Issue
- Start Page
- 19
- End Page
- 30
- ISSN
- 0973-5763
- Abstract
- This study provides a dashboard for predicting the past trade volume by using the historical data of the optimal volume according to the price and quantity when sending the tomatoes volume from the APC of the agricultural cooperatives to the wholesale market. Build a system to predict tomato volume. The analytical data analyzes the tomato trade volume of the metropolitan cities in Korea. The analysis data was analyzed using historical data on tomato trade volume in each region from 2015 to 2018, and data analysis using time series on the volume and price was carried out. © 2020 Pushpa Publishing House, Prayagraj, India.
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Related Researcher
- Youm, Se Kyoung
- College of Engineering (Department of Industrial and Systems Engineering)