Journal of KIBIM (한국BIM학회 논문집)

Korean Institute of Building Information Modeling (한국BIM학회)
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Forthcoming Big Data in Smart Cities: Experiment for Machine Learning Based Happiness Estimation in Seoul City

빅데이터를 이용한 서울시 행복지수 분석 및 예측을 위한 실험 및 고찰

  • 신동윤 (성균관대학교 건축학과) ;
  • 송유미 (성균관대학교 미래도시융합공학과)
  • Received : 2017.03.18
  • Accepted : 2017.03.20
  • Published : 2017.03.31
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Abstract

Cities have complex system composed diverse activities. The activities in cities have complex relationship that creates diverse urban phenomena. Big Data is emerging technology in order to understand such complex network. This research aims to understand such relations by analysing the diverse city indexes. 28 indexes were collected in 25 of districts in Seoul city and analysed to find a weighted correlation. By defining the correlation values of certain years, it tries to predict the missed index values, "happiness" of each districts in other years. The result presents that the overall prediction accuracy 70.25%. However, for further discussion, the result is considered that this methods may not enough to use in practice, since the data has inconstant accuracy by different learning years.

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References

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