서울시 공영주차장 군집화 및 수요 예측
Clustering of Seoul Public Parking Lots and Demand Prediction
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Purpose: This study aims to estimate the demand for various public parking lots in Seoul by clustering similar demand types of parking lots and predicting the demand for new public parking lots. Methods: We examined real-time parking information data and used time series clustering analysis to cluster public parking lots with similar demand patterns. We also performed various regression analyses of parking demand based on diverse heterogeneous data that affect parking demand and proposed a parking demand prediction model. Results: As a result of cluster analysis, 68 public parking lots in Seoul were clustered into four types with similar demand patterns. We also identified key variables impacting parking demand and obtained a precise model for predicting parking demands. Conclusion: The proposed prediction model can be used to improve the efficiency and publicity of public parking lots in Seoul, and can be used as a basis for constructing new public parking lots that meet the actual demand. Future research could include studies on demand estimation models for each type of parking lot, and studies on the impact of parking lot usage patterns on demand.
Abstract
Purpose: This study aims to estimate the demand for various public parking lots in Seoul by clustering similar demand types of parking lots and predicting the demand for new public parking lots. Methods: We examined real-time parking information data and used time series clustering analysis to cluster public parking lots with similar demand patterns. We also performed various regression analyses of parking demand based on diverse heterogeneous data that affect parking demand and proposed a parking demand prediction model. Results: As a result of cluster analysis, 68 public parking lots in Seoul were clustered into four types with similar demand patterns. We also identified key variables impacting parking demand and obtained a precise model for predicting parking demands. Conclusion: The proposed prediction model can be used to improve the efficiency and publicity of public parking lots in Seoul, and can be used as a basis for constructing new public parking lots that meet the actual demand. Future research could include studies on demand estimation models for each type of parking lot, and studies on the impact of parking lot usage patterns on demand.
참고문헌 (26)
- 조경미, "주차장 입·출차 데이터 기반 종합병원 주차특성 및 주차수요 분석-A병원 사례를 중심으로", 한국융합학회논문지, 11(9), pp.193~202 (2020), 한국융합학회[DOI]
- Choi, Younghoon., "A Study on Factors Influencing Turnover of Public Parking Lots in Incheon Metropolitan City", Incheon National University Urban Science Research Institute, 6(2), pp.29~34 (2017)
- Friggstad Z., "Exact Algorithms and Lower Bounds for Stable Instances of Euclidean K-means", Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithm, pp.2958~2972 (2019)
- 하지영, "스마트온실 경영체의 경영 효율성 및 영향요인 분석 - 전라권 딸기 재배 경영체를 중심으로-", 품질경영학회지, 49(2), pp.213~231 (2021), 한국품질경영학회[DOI]
- 허경용, "커널을 이용한 전역 클러스터링의 비선형화", 한국컴퓨터정보학회논문지, 15(4), pp.11~18 (2010), 한국컴퓨터정보학회
- 김창림, "사회연결망분석을 활용한 속성기반 데이터의 군집분석 : 구성원의 성격특성 데이터를 대상으로", 산업혁신연구, 36(2), pp.93~110 (2020), 산업개발연구소[DOI]
- Kim, Donghyun, "Dynamic Demand Matches Dynamic Supply", Planning and Policy, 415, pp.80~85 (2016)
- 김형준, "누적합 관리도를 활용한 생활인구 이상치 탐색", 품질경영학회지, 48(2), pp.241~256 (2020), 한국품질경영학회[DOI]
- 김인희, "전력 수요량에 대한 다변량 시계열 군집분석", 한국데이터정보과학회지, 32(3), pp.569~584 (2021), 한국데이터정보과학회[DOI]
- 김경섭, "K-평균 군집화 학습을 통한 심실조기수축 부정맥 리듬 평가", 한국컴퓨터정보학회논문지, 22(5), pp.65~72 (2017), 한국컴퓨터정보학회[DOI]
- 김세훈, "2차 미분 연산자를 이용한 효과적인 Dynamic Time Warping", 한국컴퓨터정보학회논문지, 16(2), pp.61~70 (2011), 한국컴퓨터정보학회
- 김성태, "동적 시간워핑을 활용한 시계열자료의 군집분석", Journal of The Korean Data Analysis Society, 20(5), pp.2319~2332 (2018), 한국자료분석학회[DOI]
- Kim, Taegyun, "The Study on Parking Lots Management According to Off-Street Parking Lots Characteristics : Focusing on Residential Development District", LHI Journal of Land, Housing, and Urban Affairs, 8(3), pp.131~143 (2017)
- 이의은, "주차정보제공을 위한 기초자료 분석연구", 대한토목학회 논문집D, 28(5), pp.639~647 (2008), 대한토목학회
- 이승훈, "TadGAN 기반 시계열 이상 탐지를 활용한 전처리 프로세스 연구", 품질경영학회지, 50(3), pp.459~471 (2022), 한국품질경영학회[DOI]
- Lee, Youngwoo, "A Study for Communication Mode of Bus Information System", Journal of The Korean Society of Industry Convergence, 11(3), pp.113~120 (2008)
- 오준걸, "도심활성화를 위한 용도별 지역연계 공영주차장 계획특성에 관한 연구 - 산타바바라시의 공영주차장 비교를 중심으로 -", 한국산학기술학회논문지, 17(3), pp.684~691 (2016), 한국산학기술학회[DOI]
- Park, Chandon, "A Study on the Analysis of the Parking Demands According to the Housing Unit Size in Apartment Complex-Focused on Apartment Complexes in Daegu City-", Journal of the Architectural Institute of Korea, 24(1), pp.550~553 (2004)
- Research on Key Priority Areas for Smart City through Citizen Demand Analysis Based on Big Data, "Park, Geoncheol", Seoul Digital Foundation, ~ (2018)
- 김득수, "광양만권 오존 발생특성 연구 - 군집분석 중심으로 -", 한국대기환경학회지, 38(2), pp.188~202 (2022), 한국대기환경학회[DOI]
- 박오성, "교통수요 추정의 신뢰도 제고를 위한시간대별 방향별 O", D 구축, 2017, pp.93, 93~104[DOI]
- "." (2008)[URL]
- 신승우, "지구 내 용도지역 면적을 고려한 노상·노외 주차수요 산정 모형 구축 연구: 대구광역시 중구를 대상으로", 대한교통학회지, 39(6), pp.711~720 (2021), 대한교통학회
- Study on Improving Parking Efficiency for Solving Parking Issues in Seoul, "Shin, Woojae", Seoul Digital Foundation, ~, pp.2020-4 (2020)
- Son, Hyeonseo, "A Study on the Development of Integrated Control System and the Problem of Parking Space Using Deep Learning in the Internet of Things Environment", Proceedings of Symposium of the Korean Institute of Communications and Information Sciences, pp.939~940 (2020)
- Yang J. J., "K-shape Clustering Algorithm for Building Energy Usage Patterns Analysis and Forecasting Model Accuracy Improvement", Energy and Buildings, 146, pp.27~37 (2017)