Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

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

Full metadata record
DC Field Value Language
dc.contributor.authorKim, C.-
dc.contributor.authorIm, C.-
dc.contributor.authorYoum, S.-
dc.date.accessioned2024-08-08T07:31:27Z-
dc.date.available2024-08-08T07:31:27Z-
dc.date.issued2020-09-
dc.identifier.issn0973-5763-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/19798-
dc.description.abstractThis 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.-
dc.format.extent12-
dc.language영어-
dc.language.isoENG-
dc.publisherPushpa Publishing House-
dc.titleAuxiliary system for prediction of trade volume using tomato big data and data mining methodology-
dc.typeArticle-
dc.publisher.location인도-
dc.identifier.doi10.17654/HMSI20019-
dc.identifier.scopusid2-s2.0-85091576436-
dc.identifier.bibliographicCitationJP Journal of Heat and Mass Transfer, v.2020, no.Special Issue, pp 19 - 30-
dc.citation.titleJP Journal of Heat and Mass Transfer-
dc.citation.volume2020-
dc.citation.numberSpecial Issue-
dc.citation.startPage19-
dc.citation.endPage30-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorAgricultural products processing center-
dc.subject.keywordAuthorData mining-
dc.subject.keywordAuthorRegression-
dc.subject.keywordAuthorTomato big data-
dc.subject.keywordAuthorTrade volume prediction-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > Department of Industrial and Systems Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Youm, Se Kyoung photo

Youm, Se Kyoung
College of Engineering (Department of Industrial and Systems Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE