Search Results - "density-based spatial clustering of applications with noise"

Identification of Earthquake Prone Zones in Sumatra using Density Based Spatial Clustering of Applications with Noise

Authors: Dwi Agustin Nuriani Sirodj Muhammad Nur Aidi Bagus Sartono et al.

Source: CAUCHY: Jurnal Matematika Murni dan Aplikasi. 10:916-928

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

Authors: Ulkar Karimova Yu Yi

Source: Journal of Astronomy and Space Sciences, Vol 41, Iss 1, Pp 35-42 (2024)

Subject Terms: sungrazing comets, density-based spatial clustering of applications with noise (dbscan) algorithm, 13. Climate action, comet categorization, Astronomy, QB1-991, solar system origins, coronagraphic observations, kreutz subgroups

Access URL: https://doaj.org/article/f592eb41dff64b329dfc61b7c5d722a3

Implementasi Algoritma Density Based Spatial Clustering of Applications with Noise (DBSCAN) pada Aplikasi Penerima Bantuan Langsung Tunai (BLT) Online di Desa Bahtera Makmur Rokan Hilir - Riau

Authors: Apriani Apriani Oris Krianto Sulaiman Antoni Antoni

Source: Hello World Jurnal Ilmu Komputer. 4:1-11

Behavior Mining for Aerial Target Based on Multi-Variant Density-Based Spatial Clustering of Applications with Noise Model

Authors: Zhiyuan Shi Zhenxiong Wu Kun Lu et al.

Source: 2025 8th International Conference on Advanced Algorithms and Control Engineering (ICAACE). :2535-2539

A new approach data processing: density-based spatial clustering of applications with noise (DBSCAN) clustering using game-theory

Authors: Uranus Kazemi Seyfollah Soleimani

Source: Soft Computing. 29:1331-1346

Enhanced Stratified Sampling-Density-Based Spatial Clustering of Applications With Noise (SS-DBSCAN) for High-Dimensional Data

Authors: Gloriana Monko Masaomi Kimura

Source: Data Science. 8

Density-Based Spatial Clustering of Applications With Noise (DBSCAN) for Probe Card Production for Advanced Quality Control of Wafer Probing Test

Authors: Chen-Fu Chien Butsayarin Suwattananuruk

Source: IEEE Transactions on Semiconductor Manufacturing. 37:567-575

Metode Density Based Spatial Clustering of Applications with Noise (DBSCAN) dalam Mengelompokkan Provinsi di Indonesia Berdasarkan Kasus Kriminalitas Tahun 2022

Authors: Syifa Miftahurrahmi null Zilrahmi Nonong Amalita et al.

Source: UNP Journal of Statistics and Data Science. 2:330-337

Kernel Density Based Spatial Clustering of Applications with Noise

Authors: Rohan Kalpavruksha Roshan Kalpavruksha Teryn Cha et al.

Source: Proceedings of the International Florida Artificial Intelligence Research Society Conference, Vol 38, Iss 1 (2025)

Subject Terms: Kernel, Technology, Electronic computers. Computer science, QA75.5-76.95, DBSCAN, Clustering

Access URL: https://doaj.org/article/4b00fb0cb16e47aeadbb3916ae8e5585

Calculation of Overhead Line Ampacity Based on Density-Based Spatial Clustering of Applications with Noise

Authors: Hao Wang Feng Zhang Guoqiang Li et al.

Source: 2024 6th International Conference on Energy, Power and Grid (ICEPG). :1192-1196

A Fréchet Distance -Hierarchical Density-based Spatial Clustering of Applications with Noise for Ship Trajectory Clustering and Route Recognition

Authors: Shuchang He Changsheng Wu

Source: 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). :1-5

Pengelompokan Data Pendistribusian Listrik Menggunakan Algoritma Density Based Spatial Clustering of Application With Noise (DBSCAN): Clustering Electricity Distribution Data Using Density-Based Spatial Clustering of Applications With Noise (DBSCAN) Algorithm

Authors: Miftah Farid Fitri Insani Surya Agustian et al.

Source: MALCOM: Indonesian Journal of Machine Learning and Computer Science. 4:1024-1033

Anomaly detection with the density based spatial clustering of applications with noise (DBSCAN) to detect potentially fraudulent wire transfers

Authors: Kim, Yongbum Vasarhelyi, Miklos A.

Source: Arias Montano. Repositorio Institucional de la Universidad de Huelva
Universidad de Huelva (UHU)

Subject Terms: 53 Ciencias Económicas, Fraud detection, Anomaly detection, DBSCN, Spatial clustering, Density based clustering, Clustering

File Description: application/pdf

Access URL: https://hdl.handle.net/10272/23589

Revolutionizing Air Quality Prognostication: Fusion of Deep Learning and Density-Based Spatial Clustering of Applications with Noise for Enhanced Pollution Prediction

Authors: Moheshkumar G Saravanan N Ravichandru T et al.

Source: 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN). :124-129

New perspective on density-based spatial clustering of applications with noise for groundwater assessment

Authors: Abdulhayat M. Jibrin Mohammad Al-Suwaiyan Zaher Mundher Yaseen et al.

Source: Journal of Hydrology. 661:133566

Structure and Density Heterogeneities of the l-3Al2O3.2SiO2 System: Insight from Computer Simulation and Density-Based Spatial Clustering of Applications with Noise

Authors: Nguyen Van Hong Mai Thi Lan Pham Tri Dung

Source: VNU Journal of Science: Mathematics - Physics. 41

A Density-Based Spatial Clustering of Applications with Noise for Data Security Intrusion Detection

Authors: Carlos Méndez Laura García Javier Torres

Source: Optimizations in Applied Machine Learning. 5

SS-DBSCAN: Semi-Supervised Density-Based Spatial Clustering of Applications With Noise for Meaningful Clustering in Diverse Density Data

Authors: Tiba Zaki Abdulhameed Suhad A. Yousif Venus W. Samawi et al.

Source: IEEE Access, Vol 12, Pp 131507-131520 (2024)

Subject Terms: unsupervised classification, semi-supervised clustering, word classification, Electrical engineering. Electronics. Nuclear engineering, DBSCAN, Clustering, TK1-9971

Access URL: https://doaj.org/article/e976f018eec84c64a332e9362892fd8e

Density based spatial clustering of applications with noise and fuzzy C-means algorithms for unsupervised mineral prospectivity mapping

Authors: Reza Ghezelbash Mehrdad Daviran Abbas Maghsoudi et al.

Source: Earth Science Informatics. 18

Enhanced Screening of Retired Lithium-Ion Batteries for Secondary Applications Using Improved K-Means Clustering and Density-Based Spatial Clustering of Applications with Noise

Authors: Byoungkuk Lee Je Yeong Lim Dong Hwan Kim