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

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

“… In this study, we introduce an automated classification technique using the density-based spatial clustering of applications with noise (DBSCAN…”
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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

“… In this study, we introduce an automated classification technique using the densitybased spatial clustering of applications with noise (DBSCAN…”
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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 by Farid, Miftah, Insani, Fitri, Agustian, Surya, Afriyanti, Liza

“… efisiensi dan konservasi energi, dan lain sebagainya.  Salah satu alat untuk mencapai tujuan tersebut adalah dengan mengelompokkan (clustering…”
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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

“…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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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

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

“…? 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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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

“…) 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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Adaptive Density-Based Spatial Clustering of Applications with Noise (ADBSCAN) for Clusters of Different Densities by Fahim, Ahmed

“… These methods can discover clusters of various shapes and sizes. The most studied algorithm in this class is the Density-Based Spatial Clustering of Applications with Noise (DBSCAN…”
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SS-DBSCAN: Epsilon Estimation with Stratified Sampling for Density-Based Spatial Clustering of Applications with Noise by Monko, Gloriana Joseph, Kimura, Masaomi

“… Among the density-based clustering algorithms, DBSCAN (Density-Based Spatial Clustering of Applications with Noise…”
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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

“…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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Semi-Automatic Detection of Ground Displacement from Multi-Temporal Sentinel-1 Synthetic Aperture Radar Interferometry Analysis and Density-Based Spatial Clustering of Applications with Noise in Xining City, China by Chen, Dianqiang, Wu, Qichen, Sun, Zhongjin, Shi, Xuguo, Zhang, Shaocheng, Zhang, Yi, Wu, Yunlong

“…The China Loess Plateau (CLP) is the world’s most extensive and thickest region of loess deposits. The inherently loose structure of loess makes the CLP…”
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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.

“…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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A maritime traffic route extraction method based on density-based spatial clustering of applications with noise for multi-dimensional data by Huang, Changhai, Qi, Xucun, Zheng, Jian, Zhu, Ranchao, Shen, Jia

“…) data and the multi-dimensional density-based spatial clustering of applications with noise (MD-DBSCAN) data…”
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Outlier identification and group satisfaction of rating experts: density-based spatial clustering of applications with noise based on multi-objective large-scale group decision-making evaluation by Zhou, Shengjia, Zhou, Junxing, Chen, Sichao

“… However, the clustering algorithm in LSGDM also has an impact on group satisfaction. Hence, this paper proposes a density-based spatial clustering of applications with noise (DBSCAN…”
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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

“… 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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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

“…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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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

“…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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Segmentation of coronary arteries from X-ray angiographic images using density based spatial clustering of applications with noise (DBSCAN) by Mardani, Kamran, Maghooli, Keivan, Farokhi, Fardad

“… This study introduces a new method for segmenting coronary arteries in X-ray angiographic images using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm…”
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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

“…), 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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GRIDBSCAN: GRId Density-Based Spatial Clustering of Applications with Noise by Uncu, O., Gruver, W.A., Kotak, D.B., Sabaz, D., Alibhai, Z., Ng, C.

“… One of the most well-known density based clustering algorithms for processing spatial data is Density-Based Spatial Clustering of Application with Noise (DBSCAN…”
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