Implementation of New Incremental Mass Clustering Algorithm to Handle Dynamic Dataset and Identify Core, Non-Core, Noisy Points-Reference-Cited by-同舟云学术

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Implementation of New Incremental Mass Clustering Algorithm to Handle Dynamic Dataset and Identify Core, Non-Core, Noisy Points

Published:2023-07-07 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES)
language:
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Author:

Babu S Mallesh¹,Sharma V.K.²,Roopa S.³

Affiliation:

1. Bhagwant University,Department of CSE,Ajmer,India

2. Bhagwant University,Department of EEE,Ajmer,India

3. Siddaganga Institute of Technology,Department of ECE,Tumakuru,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199115/10199221/10200794.pdf?arnumber=10200794

Reference30 articles.

1. Data-Driven Trajectory Quality Improvement for Promoting Intelligent Vessel Traffic Services in 6G-Enabled Maritime IoT Systems

2. Multivariate weather anomaly detection using DBSCAN clustering algorithm;wibisono;Journal of Physics Conference Series vol 1869 2nd Annual Conference of Science and Technology (ANCOSET 2020),2020

3. Density-based clustering of static and dynamic functional MRI connectivity features obtained from subjects with cognitive impairment

4. Feature selection based intrusion detection system using the combination of DBSCAN, K-Mean++ and SMO algorithms

5. A survey of density based clustering algorithms

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