Ajou University repository

Prediction of Dangerous Areas for Food Desertification in Gyeonggi Province
  • Kim, Sehyoung ;
  • Cheon, Seyeon ;
  • Park, Jae Hyeong ;
  • Park, Seongwoo ;
  • Kim, Haesung ;
  • Kang, Juyoung
Citations

SCOPUS

0

Citation Export

DC Field Value Language
dc.contributor.authorKim, Sehyoung-
dc.contributor.authorCheon, Seyeon-
dc.contributor.authorPark, Jae Hyeong-
dc.contributor.authorPark, Seongwoo-
dc.contributor.authorKim, Haesung-
dc.contributor.authorKang, Juyoung-
dc.date.issued2022-01-01-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/36814-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85143255249&origin=inward-
dc.description.abstractFood desertification refers to a phenomenon in which it has become difficult to obtain fresh food including vegetables in the community. In the past, research on food desertification risk areas has not been conducted properly in Korea. Since the phenomenon of food desertification is accelerating due to the increase of single-person households and the elderly, research on food desertification is needed to solve and prevent food desertification. In addition, so far, food desertification studies have been conducted only to the extent of deriving case studies and food desertification areas, but no research has been conducted to predict this. In this study, food desertification risk areas were derived, and a predictive model was produced to prevent this.-
dc.language.isoeng-
dc.publisherIEEE Computer Society-
dc.subject.meshCase-studies-
dc.subject.meshDangerous area-
dc.subject.meshDesertification risk-
dc.subject.meshFood desertification-
dc.subject.meshFresh food-
dc.subject.meshMachine-learning-
dc.subject.meshPredictive models-
dc.subject.meshPrevention of food desertification-
dc.subject.meshRisk areas-
dc.titlePrediction of Dangerous Areas for Food Desertification in Gyeonggi Province-
dc.typeConference-
dc.citation.conferenceDate2022.10.19. ~ 2022.10.21.-
dc.citation.conferenceName13th International Conference on Information and Communication Technology Convergence, ICTC 2022-
dc.citation.editionICTC 2022 - 13th International Conference on Information and Communication Technology Convergence: Accelerating Digital Transformation with ICT Innovation-
dc.citation.endPage2100-
dc.citation.startPage2098-
dc.citation.titleInternational Conference on ICT Convergence-
dc.citation.volume2022-October-
dc.identifier.bibliographicCitationInternational Conference on ICT Convergence, Vol.2022-October, pp.2098-2100-
dc.identifier.doi10.1109/ictc55196.2022.9952669-
dc.identifier.scopusid2-s2.0-85143255249-
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/conferences.jsp-
dc.subject.keywordBig Data-
dc.subject.keywordData Analysis-
dc.subject.keywordFood Desertification-
dc.subject.keywordMachine Learning-
dc.subject.keywordPrevention of food desertification-
dc.type.otherConference Paper-
dc.description.isoafalse-
dc.subject.subareaInformation Systems-
dc.subject.subareaComputer Networks and Communications-
Show simple item record

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

Related Researcher

Kang, Ju Young Image
Kang, Ju Young강주영
Department of Business Intelligence
Read More

Total Views & Downloads

File Download

  • There are no files associated with this item.