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      A study on density based spatial clustering of applications with noise​

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      ScienceOpen Posters
      ScienceOpen
      DBSCAN, Noise, Spatial Data, Algorithms, Machine Learning, Outliers, Artificial Intelligence, Neighborhood, Clustering, Density
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            Abstract

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            Author and article information

            Journal
            ScienceOpen Posters
            ScienceOpen
            19 September 2023
            Affiliations
            [1 ] Symbiosis Institute of Technology, Symbiosis International University, Pune, Maharashtra, India;
            Author notes
            Author information
            https://orcid.org/0009-0008-4384-2941
            Article
            10.14293/P2199-8442.1.SOP-.PQUWPP.v1
            40af40c5-78a5-46b4-bf98-2a5aa07d51b9

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            History
            : 19 September 2023
            Categories

            Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            Artificial intelligence
            DBSCAN,Noise,Spatial Data,Algorithms,Machine Learning,Outliers,Artificial Intelligence,Neighborhood,Clustering,Density

            References

            1. DiFrancesco Paul-Mark, Bonneau David, Hutchinson D. Jean. The Implications of M3C2 Projection Diameter on 3D Semi-Automated Rockfall Extraction from Sequential Terrestrial Laser Scanning Point Clouds. Remote Sensing. Vol. 12(11)2020. MDPI AG. [Cross Ref]

            2. Fauzan Achmad, Novianti Afdelia, Ramadhani Raden Rara Mentari Ayu, Adhiwibawa Marcelinus Alfafisurya Setya. Analysis of Hotels Spatial Clustering in Bali: Density-Based Spatial Clustering of Application Noise (DBSCAN) Algorithm Approach. EKSAKTA: Journal of Sciences and Data Analysis. 25–38. 2022. Universitas Islam Indonesia (Islamic University of Indonesia). [Cross Ref]

            3. WANG Gui-zhi, WANG Guang-liang. Improved fast DBSCAN algorithm. Journal of Computer Applications. Vol. 29(9):2505–2508. 2009. China Science Publishing & Media Ltd. [Cross Ref]

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