LikeSNU 서울대학교 도서관
SNU Big Data Knowledge Information Platform

Full Menu

AI
Report registration
  • Type
  • Title
  • Group
  • Link
  • Thumbnail
Paper List
Paper List (0Count) Export to Excel

There is no data.

모바일폰 위치기반 생활이동 빅데이터를 활용한 통행목적별 도시활력 영향요인 분석 : PageRank 알고리즘과 SHAP 기계학습을 활용하여

Author
박준상, 김선재, 이수기
Journal Title
국토계획
Publication Year
2022
Summary

This study analyzes the determining factors of urban vitality by travel purpose using mobile phone location-based big data, the PageRank algorithm, and interpretable machine learning techniques. The factors influencing urban vitality differ between commuting and non-commuting travel, with street scenery significantly impacting non-commuting travel vitality but not commuting travel. Restaurant and subway station density show positive correlations with urban vitality for both leisure and utility travel, and street safety is a significant variable regardless of travel purpose.

Quotation Papers(0)

List of papers cited by this paper

Thesis Indicator

Related Content

LikeSNU analyzes your query semantically to recommend related resources.

Previous
Next

The attraction gradient of urban functions: How does functional mix at multiple scales predict urban vitality

Duan, Jishan; Wang, Hui; Liu, Lun; Zhang, Jie · 2025

CITIES

서울시 연령대별 비통근 통행 집중지역 특성 분석 : 생활이동 데이터를 활용하여 Analysis of Characteristics of Non-commuting Travel Concentration Areas in Seoul by Age Group : Utilizing Mobile Phone-based Mobility Data

김예진; 이수기; 하정원 · 2024

국토계획

Examining active travel behavior through explainable machine learning: Insights from Beijing, China

Yin, Ganmin; Huang, Zhou; Fu, Chen; Ren, Shuliang; Bao, Yi; Ma, Xiaolei · 2024

TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT

Previous
Next
TOP