Auxiliary system for prediction of trade volume using tomato big data and data mining methodology

Changgyun Kim, Chaemin Im, Sekyoung Youm

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)19-30
Number of pages12
JournalJP Journal of Heat and Mass Transfer
Volume2020
Issue numberSpecial Issue
DOIs
StatePublished - 2020

Keywords

  • Agricultural products processing center
  • Data mining
  • Regression
  • Tomato big data
  • Trade volume prediction

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