Search Results - Density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm

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  1. 1

    Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm by Karimova, Ulkar, Yi, Yu

    ISSN: 2093-5587, 2093-1409
    Published: The Korean Space Science Society 01.03.2024
    Published in Journal of astronomy and space sciences (01.03.2024)
    “… In this study, we introduce an automated classification technique using the density-based spatial clustering of applications with noise (DBSCAN…”
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    Journal Article
  2. 2

    Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm by Ulkar Karimova, Yu Yi

    ISSN: 2093-5587, 2093-1409
    Published: 2024
    “… In this study, we introduce an automated classification technique using the densitybased spatial clustering of applications with noise (DBSCAN…”
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    Journal Article
  3. 3

    Research on multi-label classification method of transformer based on DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm by Wang, MingYu, Cheng, Rui

    ISSN: 1742-6588, 1742-6596
    Published: IOP Publishing 01.12.2021
    Published in Journal of physics. Conference series (01.12.2021)
    “…With the improvement of the intelligent level of power grid and the enhancement of the integrated characteristics of power grid, the degree of discretization…”
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    Journal Article
  4. 4

    Analysis of Hotels Spatial Clustering in Bali: Density-Based Spatial Clustering of Application Noise (DBSCAN) Algorithm Approach by Fauzan, Achmad, Novianti, Afdelia, Ramadhani, Raden Rara Mentari Ayu, Adhiwibawa, Marcelinus Alfafisurya Setya

    ISSN: 2720-9326, 2716-0459
    Published: 07.03.2022
    “… If the point distribution pattern is more towards the cluster, it is continued with the Density-Based Spatial Clustering of Application…”
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    Journal Article
  5. 5

    Use Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Algorithm to Identify Galaxy Cluster Members by Zhang, Mingrui

    ISSN: 1755-1307, 1755-1315, 1755-1315
    Published: Bristol IOP Publishing 09.07.2019
    “…? How to ensure the correctness of classification? Based on the results of CoDECS numerical simulation and combining DBSCAN algorithm, this paper attempts to classify the data and compare and explain the results of the three methods…”
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    Journal Article
  6. 6
  7. 7

    Fault Diagnosis in Gas Insulated Switchgear Based on Genetic Algorithm and Density- Based Spatial Clustering of Applications With Noise by Yang, Yuan, Suliang, Ma, Jianwen, Wu, Bowen, Jia, Weixin, Li, Xiaowu, Luo

    ISSN: 1530-437X, 1558-1748
    Published: New York IEEE 15.01.2021
    Published in IEEE sensors journal (15.01.2021)
    “…) consisting of a feature selection method based on genetic algorithm (GA) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN…”
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    Journal Article
  8. 8

    A novel adaptive density-based spatial clustering of application with noise based on bird swarm optimization algorithm by Wang, Limin, Wang, Honghuan, Han, Xuming, Zhou, Wei

    ISSN: 0140-3664, 1873-703X
    Published: Elsevier B.V 01.06.2021
    Published in Computer communications (01.06.2021)
    “… To solve the above problem, we propose a novel adaptive density-based spatial clustering of application with noise based on bird swarm optimization algorithm (BSA-DBSCAN…”
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    Journal Article
  9. 9

    Implementation of K-Nearest Neighbor Algorithm on Density-Based Spatial Clustering Application with Noise Method on Stunting Clustering by Gani, Friansyah, Panigoro, Hasan S., Mahmud, Sri Lestari, Rahmi, Emli, Nasib, Salmun K., Nashar, La Ode

    ISSN: 2775-9644, 2775-9644
    Published: Universitas Nusa Cendana 01.11.2024
    Published in Jurnal Diferensial (01.11.2024)
    “…This paper studies the implementation of the K-Nearest Neighbor (KNN) algorithm on Density-Based Spatial Clustering Application with Noise (DBSCAN…”
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    Journal Article
  10. 10

    Improved Density Based Spatial Clustering of Applications of Noise Clustering Algorithm for Knowledge Discovery in Spatial Data by Sharma, Arvind, Tiwari, Akhilesh, Gupta, R. K.

    ISSN: 1024-123X, 1563-5147
    Published: Cairo, Egypt Hindawi Limiteds 01.01.2016
    Published in Mathematical Problems in Engineering (01.01.2016)
    “…There are many techniques available in the field of data mining and its subfield spatial data mining is to understand relationships between data objects…”
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    Journal Article
  11. 11

    Density based spatial clustering of applications with noise and fuzzy C-means algorithms for unsupervised mineral prospectivity mapping by Ghezelbash, Reza, Daviran, Mehrdad, Maghsoudi, Abbas, Hajihosseinlou, Mahsa

    ISSN: 1865-0473, 1865-0481
    Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2025
    Published in Earth science informatics (01.02.2025)
    “…Our research focuses on examining two clustering methods, namely Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and fuzzy c-means (FCM…”
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    Journal Article
  12. 12

    An Adaptive Clustering Scheme Based on Modified Density-Based Spatial Clustering of Applications with Noise Algorithm in Ultra-Dense Networks by Ren, Yuting, Xu, Rongtao

    ISSN: 2577-2465
    Published: IEEE 01.09.2019
    Published in IEEE Vehicular Technology Conference (01.09.2019)
    “…), which has been proven to effectively eliminate interference. Two machine learning algorithms, Density-Based Spatial Clustering of Applications with Noise (DBSCAN…”
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    Conference Proceeding
  13. 13

    Mapping National-Scale Croplands in Pakistan by Combining Dynamic Time Warping Algorithm and Density-Based Spatial Clustering of Applications with Noise by Guo, Ziyan, Yang, Kang, Liu, Chang, Lu, Xin, Cheng, Liang, Li, Manchun

    ISSN: 2072-4292, 2072-4292
    Published: Basel MDPI AG 01.11.2020
    Published in Remote sensing (Basel, Switzerland) (01.11.2020)
    “… This study proposes an automatic cropland extraction method based on the DTW algorithm and density-based spatial clustering of applications with noise (DBSCAN…”
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    Journal Article
  14. 14

    Underwater Sensor Network Deployment Algorithm Using Density-based Spatial Clustering of Applications with Noise by Wang, Hui, Chang, Tingcheng, Fan, Yexian, Li, Zhiliang

    ISSN: 0914-4935
    Published: Tokyo MYU Scientific Publishing Division 01.01.2019
    Published in Sensors and materials (01.01.2019)
    “… We propose a fish-swarm-inspired underwater sensor network deployment algorithm using density-based spatial clustering of applications with noise (DBSCAN…”
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    Journal Article
  15. 15

    A Comparative Study between of Fuzzy C-Means Algorithms and Density based Spatial Clustering of Applications with Noise by Kyu Lee, Kwang, ., .

    ISSN: 2227-524X, 2227-524X
    Published: 2018
    “…] is a very important clustering technique based on fuzzy logic. DBSCAN(Density Based Spatial Clustering of Applications with Noise)[8…”
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    Journal Article
  16. 16

    Study of clustered damage in DNA after proton irradiation based on density-based spatial clustering of applications with noise algorithm by Tang, Jing, Zhang, Pengcheng, Xiao, Qinfeng, Li, Jie, Gui, Zhiguo

    ISSN: 1001-5515
    Published: China 25.08.2019
    Published in Sheng wu yi xue gong cheng xue za zhi (25.08.2019)
    “… Therefore, this work presents a density-based spatial clustering of applications with noise (DBSCAN…”
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    Journal Article
  17. 17

    A Complexity Survey on Density based Spatial Clustering of Applications of Noise Clustering Algorithms by Hassan, Boulchahoub, Zineb, Rachiq, Amine, Labriji, Elhoussine, Labriji

    ISSN: 2158-107X, 2156-5570
    Published: West Yorkshire Science and Information (SAI) Organization Limited 2021
    “… Up to now, many algorithms were developed for clustering using several techniques including centroids, density and dendrograms approaches…”
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    Journal Article
  18. 18

    An Improved Density-Based Spatial Clustering of Applications with Noise Algorithm with an Adaptive Parameter Based on the Sparrow Search Algorithm by Huang, Zicheng, Liang, Zuopeng, Zhou, Shibo, Zhang, Shuntao

    ISSN: 1999-4893, 1999-4893
    Published: Basel MDPI AG 01.05.2025
    Published in Algorithms (01.05.2025)
    “…The density-based spatial clustering of applications with noise (DBSCAN) is able to cluster arbitrarily structured datasets…”
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    Journal Article
  19. 19

    Modification of a Density-Based Spatial Clustering Algorithm for Applications with Noise for Data Reduction in Intrusion Detection Systems by Wiharto, Wiharto, Wicaksana, Aditya K., Cahyani, Denis E.

    ISSN: 1598-2645, 2093-744X
    Published: 한국지능시스템학회 2021
    “… This study proposes an IDS model that combines DBSCAN modification with the CART algorithm…”
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    Journal Article
  20. 20

    SS-DBSCAN: Semi-Supervised Density-Based Spatial Clustering of Applications With Noise for Meaningful Clustering in Diverse Density Data by Zaki Abdulhameed, Tiba, Yousif, Suhad A., Samawi, Venus W., Imad Al-Shaikhli, Hasnaa

    ISSN: 2169-3536, 2169-3536
    Published: IEEE 2024
    Published in IEEE access (2024)
    “…DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised clustering algorithm designed to identify clusters of various shapes and sizes in noisy datasets by pinpointing core points…”
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    Journal Article