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NTIS 바로가기한국지형공간정보학회지 = Journal of the korean society for geospatial information science, v.25 no.4, 2017년, pp.97 - 106
이민혁 (서울시립대학교 공간정보공학과) , 전인우 (서울시립대학교 공간정보공학과) , 전철민 (서울시립대학교 공간정보공학과)
This study proposes a method to cluster public transit stops using an improved DBSCAN algorithm to build microscopic traffic zones. The classic DBSCAN algorithm considers only the distance between two stops when determining the neighbor relationship. The proposed DBSCAN algorithm determines the neig...
Ester, M., Kriegel, H. P., Sander, J. and Xu, X., 1996, A density-based algorithm for discovering clusters in large spatial databases with noise, Kdd, Vol. 96, No. 34, pp. 226-231.
Hartigan, J. A. and Wong, M. A., 1979, Algorithm AS 136: A k-means clustering algorithm, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 28, No. 1, pp. 100-108.
Kieu, L. M., Bhaskar, A. and Chung, E., 2015, A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data, Transportation Research Part C: Emerging Technologies, Vol. 58, pp. 193-207.
Kim, D. H. and Park, D. J., 2015, A study on Customer-Oriented Measure Methodology of Public Transport Accessibility Under Time and Space Constraints, The 73rd Conference of Korean Society of Transportation, pp. 545-550.
Lee, S., Hickman, M. and Tong, D., 2012, Stop Aggregation Model: Development and Application, Transportation Research Record: Journal of the Transportation Research Board, No. 2276, pp. 38-47.
Luo, D., Cats, O. and van Lint, H., 2017, Constructing Transit Origin-Destination Matrices with Spatial Clustering, Transportation Research Record: Journal of the Transportation Research Board, No. 2652, pp. 39-49.
Oh, G. H., 2017, Techniques and Applications of Classification and Clustering of Big Time-Series Data, Ph. D. dissertation, Kyunghee University, pp. 16-18.
Tran, T. N., Drab, K. and Daszykowski, M., 2013, Revised DBSCAN algorithm to cluster data with dense adjacent clusters, Chemometrics and Intelligent Laboratory Systems, Vol. 120, pp. 92-96.
Yujian, L. and Bo, L., 2007, A normalized Levenshtein distance metric, IEEE transactions on pattern analysis and machine intelligence, Vol. 29, No. 6, pp. 1091-1095.
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