Unite and conquer approach for data clustering based on particle swarm optimization and moth flame optimization by E. Mosavi, S.A. Shahzadeh Fazeli, E. Abbasi, F. Kaveh-Yazdy

“…A prominent clustering technique is the k-means algorithm, which assigns data objects to the nearest cluster center. …”
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Unveiling insights from unstructured wealth: a comparative analysis of clustering techniques on blockchain cryptocurrency data by Ramzi A. Haraty, Salma Sobeh

“…This survey examines seven widely recognized clustering techniques, namely<em> k</em>-means, <em>G</em>-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and <em>k</em>-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and <em>k</em>-means clustering algorithm and compares them with a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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Research on management mode of talent team in E-government based on big data analysis by Shixuan Hao

“…Compared with other data mining algorithms such as association rule data mining based on K-means algorithm, the combination of decision tree and improved Apriori algorithm has lower operational errors and more obvious operational efficiency in the management of E-government talent team. …”
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A Improving House Price Clustering Results with K-means through the Implementation of One-hot Encoding Pre-processing Technique by Vicka Rizqi Maulani, Mula Agung Barata, Pelangi Eka Yuwita

“…The 0.15 matrix result is relatively low, which is caused by the overlap of house price values in the dataset, but it has been shown that one-hot encoding can represent categorical data well in the data pre-processing process so that the data can be processed with the k-means algorithm.…”
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DPLQ: Location‐based service privacy protection scheme based on differential privacy by Qingyun Zhang, Xing Zhang, Mingyue Wang, Xiaohui Li

“…The users' location privacy protection algorithm divides the map using the Voronoi diagram, choosing l fake location points based on the improved k‐means algorithm and l‐diversity idea, and protects users' location privacy with the Laplace mechanism. …”
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Innovation in Manufacturing Within the Digital Intelligence Context: Examining Faultlines Through Information Processing by Kangli Zhang, Jinwei Zhu

“…Using panel data from A-Share manufacturing listed companies between 2015 and 2023, we conducted programming in the R language employing hierarchical clustering and k-means algorithms for faultline grouping calculations. The empirical analysis portion utilized STATA software, where the Hausman test was implemented to determine the use of a fixed-effects model for computation. …”
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Mean Squared Error Representative Points of Pareto Distributions and Their Estimation by Xinyang Li, Xiaoling Peng

“…We demonstrate the uniqueness and existence of these representative points under certain parameter settings and provide a theoretical k-means algorithm for the computation of MSE-RPs for Pareto I and Pareto II distributions. …”
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The Sakhalin Ainu: origin and population contacts according to cranial-metric data by Moiseyev V.G., Zubova A.V.

“…We analyzed individual cranial metric data on the Sakhalin Ainu, the Hokkaido Ainu, and several ancient and historical samples from the Far East region using canonical variate analysis with subsequent clustering of the CVs scores with K-means algorithm. The results revealed high level of morphological diversity of the Sakhalin Ainu sample. …”
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Presenting the detection algorithm of all types of vessels in the Persian Gulf region using radar images in order to improve the security of navigation by Ali Hanafi, Mehdi Keykhaee

“…In this research, Sentinel-1 radar sensor images were used, and finally, using K-means algorithm, 365 training samples of the sea and ships in the Persian Gulf were prepared in different weather conditions. 70% of it is introduced to the network as training data and 30% as test data. …”
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Clusters from chronic conditions in the Danish adult population. by Anders Stockmarr, Anne Frølich

“…We use algorithmic diagnoses and the K-means algorithm to cluster the entire 2015 Danish multimorbidity population into 5 clusters. …”
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MULTI-TEMPORAL ANALYSIS OF LAND USE CHANGE IN THE MAGDALENA TEQUISISTLAN MICRO-BASIN, OAXACA, MEXICO by Juan Ángel García-Aguilar, Rufino Sandoval García, José Raymundo Enríquez-del Valle, Gerardo Rodríguez-Ortiz, José Cristóbal Leyva López, Judith Martínez de la Cruz

“…Supervised classification was performed with Quantum Gis® 3.6.0 "Maidenhead" software and the K-Means algorithm was used for atmospheric correction, while concordance and precision were calculated with the Kappa index. …”
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Amharic document clustering using semantic information from neural word embedding and encyclopedic knowledge by Dessalew Yohannes, Yenewondim Biadgie Sinshaw, Surafiel Habib Asefa, Yaregal Assabie

“…Finally, documents are clustered based on this matrix using the spherical k-means algorithm. The proposed system is tested using an Amharic text corpus and the Amharic Wikipedia which is utilized as encyclopedic knowledge. …”
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Enhancing structural health monitoring with machine learning for accurate prediction of retrofitting effects by A. Presno Vélez, M. Z. Fernández Muñiz, J. L. Fernández Martínez

“…Unsupervised principal component analysis (PCA) projections and a K-means algorithm achieved $ 70 \% $ accuracy in differentiating data before and after retrofitting. …”
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Automatic Acne Detection Model Based on Improved YOLOv7 by Delong Zhang, Chunyang Jin, Zhidong Zhang, Xiyuan Cao, Chenyang Xue

“…Finally, the initial anchor boxes of YOLOv7 are adjusted by the K-Means algorithm to make the model more suitable for acne detection. …”
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Secure cloud computing: leveraging GNN and leader K-means for intrusion detection optimization by Raman Dugyala, Premkumar Chithaluru, M. Ramchander, Sunil Kumar, Arvind Yadav, N. Sudhakar Yadav, Diaa Salama Abd Elminaam, Deema Mohammed Alsekait

“…Key contributions of this work include the integration of the Leader K-means algorithm for effective data clustering, improving the IDS’s ability to differentiate between normal and malicious activities. …”
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Historical Manuscripts Analysis: A Deep Learning System for Writer Identification Using Intelligent Feature Selection with Vision Transformers by Merouane Boudraa, Akram Bennour, Mouaaz Nahas, Rashiq Rafiq Marie, Mohammed Al-Sarem

“…We utilize the FAST detector for feature detection, extracting keypoints representing handwriting styles, followed by clustering with the k-means algorithm to obtain meaningful patches of uniform size. …”
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Optimizing Inotropic Infusion With Cluster Specific AI Decision Models and Digital Twins by Vidya S Nair, G. D. Heshan Niranga, Aryalakshmi C.S, Dipu T. Sathyapalan, Thushara Madathil, Rahul Krishnan Pathinarupothi

“…This approach captures variability in drug responses through clustering of patients using LSTM autoencoders and K-means algorithms, subsequently developing LSTM-based decision models for infusion rates tailored to clusters. …”
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Exploring trans-regional harvesting operation patterns based on multi-scale spatiotemporal partition using GNSS trajectory data by Daoye Zhu, Boyong Xiao, Haoling Xie, Dong Li, Haitong He, Weixin Zhai

“…By designing multiscale grids and temporal partitions, we efficiently processed high-dimensional trajectory data by employing t-SNE and K-means++ algorithms for dimensionality reduction and clustering, and the visualization validated the clustering effectiveness. …”
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Voltage optimization strategy for active distribution network based on distributed photovoltaic cluster control by Chunrong JIANG, Bowen ZHU, Xufeng ZHOU, Jiani LU, Aidong ZENG

“…Subsequently, the approximate voltage sensitivity is calculated based on the day-ahead scheduling results, and clusters are partitioned using the K-means algorithm according to a comprehensive clustering index. …”
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Growth Curve Models and Clustering Techniques for Studying New Sugarcane Hybrids by Carlos David Carretillo Moctezuma, María Guzmán Martínez, Flaviano Godínez-Jaimes, José C. García-Preciado, Ramón Reyes Carreto, José Terrones Salgado, Edgar Pérez Arriaga

“…According to the Connectivity and Dunn indexes, the DBSCAN algorithm provides the best clustering structure for materials in the plant cycle, while for the ratoon cycle, the k-means algorithm offers the best clustering structure. …”
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