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Prediction of Dangerous Areas for Food Desertification in Gyeonggi Province
  • Kim, Sehyoung ;
  • Cheon, Seyeon ;
  • Park, Jae Hyeong ;
  • Park, Seongwoo ;
  • Kim, Haesung ;
  • Kang, Juyoung
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Publication Year
2022-01-01
Journal
International Conference on ICT Convergence
Publisher
IEEE Computer Society
Citation
International Conference on ICT Convergence, Vol.2022-October, pp.2098-2100
Keyword
Big DataData AnalysisFood DesertificationMachine LearningPrevention of food desertification
Mesh Keyword
Case-studiesDangerous areaDesertification riskFood desertificationFresh foodMachine-learningPredictive modelsPrevention of food desertificationRisk areas
All Science Classification Codes (ASJC)
Information SystemsComputer Networks and Communications
Abstract
Food 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.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36814
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85143255249&origin=inward
DOI
https://doi.org/10.1109/ictc55196.2022.9952669
Journal URL
http://ieeexplore.ieee.org/xpl/conferences.jsp
Type
Conference
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