Methods for Cognitive Diagnosis of Students’ Abilities Based on Keystroke Features by Xu Chi, Xinyu Guo, Yu Sheng

“…Keystroke data were used to obtain students’ programming behavior information and optimize the traditional clustering algorithm according to the characteristics of keystroke data. The K-means++ algorithm was adopted to determine the initial clustering centers, the elbow method was used to determine the number of clusters, and an outlier processing algorithm was introduced. …”
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Intelligent resource allocation in internet of things using random forest and clustering techniques by Nahideh Derakhshanfard, Lida Hosseinzadeh, Fahimeh Rashid Jafari, Ali Ghaffari

“…Initially, IoT devices are grouped using the K-Means algorithm based on features such as energy consumption and bandwidth requirements. …”
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Multi-Factor Load Classification Method considering Clean Energy Power Generation by Yuxiu Zang, Weichun Ge, Shunjiang Wang, Yan Zhao, Tianfeng Chu

“…Based on the load characteristics, the K-means algorithm is used for main clustering. Then, the confidence level of the uncertainty of the actual load adjustable capacity is analyzed by quantifying the load adjustable potential index and the fuzzy C-means clustering method was used for secondary clustering of the adjustable capacity. …”
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Fuzzy Clustering Approaches Based on Numerical Optimizations of Modified Objective Functions by Erind Bedalli, Shkelqim Hajrulla, Rexhep Rada, Robert Kosova

“…The classical Fuzzy C-Means algorithm operates as an iterative procedure that minimizes an objective function defined based on the weighted distance between each point and the cluster centers. …”
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Dementia Scale Score Classification Based on Daily Activities Using Multiple Sensors by Akira Minamisawa, Shogo Okada, Ken Inoue, Mami Noguchi

“…The experimental results show that a maximum accuracy of 0.871 was obtained with a linear support vector machine (SVM) model by fusing the door, location, and sleep features and by clustering activity patterns using the X-means algorithm.…”
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Transcranial High-Frequency Terahertz Stimulation Alleviates Anxiety-like Behavior in Mice via a Noninvasive Approach by Pan Wang, Chaoyang Tan, Wenyu Peng, Zekun Yan, Wenrui Jiang, Han Zhao, Huaxing Si, Jingchen Jia, Chunkui Zhang, Jian Wang, Yuchen Tian, Kun Chen, Yuefan Yang, Zhenyu Wu, Kangning Xie, Yuanming Wu, Mingming Zhang, Tao Chen

“…Mice were subjected to acute restraint stress to induce anxiety and then clustered into anxiety-susceptible and anxiety-resilient groups using the K-means algorithm. We developed an anxiety phenotype prediction classifier utilizing the naïve Bayes algorithm to accurately categorize mice. …”
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Short Term Photovoltaic Power Combination Prediction Method Based on Similar Day Selection and Data Reconstruction by Qingbin CHEN, Genghuang YANG, Liqing GENG, Juan SU, Jingsheng SUN

“…Firstly, clustering analysis of photovoltaic power is performed using the kernel fuzzy C-means algorithm, and the main influencing features are extracted through the maximum information coefficient. …”
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Data sharing and GRA weight optimization for power prediction of distributed photovoltaic power plant considering missing NWP information by YANG Xiyun, YANG Yan, MENG Lingzhuochao, PENG Yan, WANG Chenxu

“…On this basis, this paper proposes a power prediction model for distributed photovoltaic power plant based on data sharing and grey relation analysis (GRA) weight optimization. Firstly, the K-means algorithm is used to cluster the output spatial correlation of photovoltaic power plants, and GRA is used to optimize the weight of the reference power station, and the output of the target power station with missing NWP data is predicted by one-dimensional convolutional neural network (1DCNN). …”
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Experimental Demonstration of 73 Gb/s QPSK and 150 Gb/s QAM-32 Wireless Data Links in the Sub-THz Band Through Frequency Selective Surface Filters by Walter Fuscaldo, Daniele Pirrone, Dimitrios C. Zografopoulos, Antonio Ferraro, Pascal Szriftgiser, Guillaume Ducournau, Romeo Beccherelli

“…Measurement results for the EVM are predicted through an innovative use of the k-means algorithm which is here suitably modified to deal with FSS-based communications. …”
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Marine fish species recognition based on improved YOLOv5s by ZHANG Haifeng, LU Xinchun, FENG Bo, YANG Jin

“…ObjectiveIn order to improve the recognition accuracy of different kinds of marine fish, an improved YOLOv5s marine fish species recognition method was proposed.MethodsK⁃means++algorithm was used to cluster the real frames of marine fish, and more matching anchor frames were obtained with the self built data set. …”
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Research on Cognitive Radio Non-orthogonal Multiple Access System in 5G Communications Oriented to Ubiquitous Power Internet of Things by Rui SHE, Ningchi ZHANG, Yanru WANG, Dandan GUO, Wenjie MA, Hui LIU, Jie ZHANG

“…The closed expressions of spectrum access probability and throughput are derived; in order to further increase the accuracy of the classification results, an improved K-means algorithm is proposed. The alternate iterative algorithm is implemented to jointly optimize the detection time, node power and the number of user clusters such that the system throughput can be maximized eventually. …”
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Construction of a digital twin model for incremental aggregation of multi type load information in hybrid microgrids under integrity constraints by Yibo Lai, Libo Fan, Weiyan Zheng, Rongjie Han, Kai Liu

“…Based on these, establish a digital twin model for the incremental aggregation of multiple load information in a hybrid microgrid, and solve the model using an improved K-means algorithm to achieve continuous updating and optimization of load information. …”
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Safety Risk Assessment and Classification of Cadmium in Grain Processing Products by Qingchuan Zhang, Wenjie Dou, Zheng Wang, Xuemei Xu, Tongqiang Jiang

“…By analyzing the cadmium levels in processed grain products across 20 provinces and cities in China during the period 2023–2024, we have developed an improved k-means++ algorithm that determines the optimal clustering number through a voting scheme. …”
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Spatial Characteristics and Influence of Topography and Synoptic Systems on PM2.5 in the Eastern Monsoon Region of China by Shengli Zhu, Zhaowen Wang, Kai Qu, Jun Xu, Ji Zhang, Haiyi Yang, Wenxin Wang, Xiao Sui, Min Wei, Houfeng Liu

“…According to synoptic systems, regional PM2.5 pollution episodes were classified into three categories, including Uniform Pressure field (UP, 60.00%), Pre-High Pressure (PreHP, 30.91%) and Inverted-Trough (IT, 9.09%). The K-Means algorithm combined with the HYSPLIT backward trajectory clustering analysis indicated four clusters under UP controlled, and under weak pressure field was responsible for the elevation of PM2.5 concentration, where the Beijing-Tianjin-Hebei and its surrounding areas were the most polluted region. …”
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Proposing a New Method for Customer Segmentation Based on Their Level of Loyalty and Defining Appropriate Strategies for Each Segment by Samira KHodabandehlou, Ali Akbar Niknafs

“…The obtained data have been analyzed using Clementine 14.2 software application using MLP and RBF neural networks as well as the K-means algorithm. The results of the study show that the proposed method provides the highest level of accuracy for predicting the customers’ loyalty. …”
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An Efficient MapReduce-Based Parallel Clustering Algorithm for Distributed Traffic Subarea Division by Dawen Xia, Binfeng Wang, Yantao Li, Zhuobo Rong, Zili Zhang

“…Specifically, we first modify the distance metric and initialization strategy of K-Means and then employ a MapReduce paradigm to redesign the optimized K-Means algorithm for parallel clustering of large-scale taxi trajectories. …”
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Network toxicology and molecular docking reveal key mechanisms of domoic acid neurotoxicity with bio-layer interferometry validation by Dongyao Wang, Yiping Liu, Shitao Chen, Diya Lv, Yuxiao Tang, Yan Liu, Wen Yang, Hui Shen, Lianghua Wang, Feng Lu

“…Further refinements via STRING and Cytoscape software highlight the protein-protein interactions. 30 targets were recognized by both the K-means algorithm and topological analysis. GO and KEGG pathway analysis conducted through DAVID databases reveals that these targets of amnesia and neurotoxicity are predominantly enriched in multiple pathways. …”
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Roads Infrastructure Digital Twin: Advancing Situational Awareness Through Bandwidth-Aware 360° Video Streaming and Multi-View Clustering by Oussama El Marai, Sotirios Messinis, Nikolaos Doulamis, Tarik Taleb, Jukka Manner

“…The proposed framework leverages the multi-view spectral clustering approach and the K-Means++ algorithms to ensure efficient clustering of vehicles based on their GPS coordinates. …”
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Comparison of clustering methods and conventional approaches for geological fracture analysis: A case study in northern Shiraz, Iran by HAJAR KAZEMI, KOUROS YAZDJERDI, ABDOLMAJID ASADI, MOHAMMAD REZA MOZAFARI

“…The primary aim is to enhance fracture classification accuracy by integrating the k-means algorithm with a genetic algorithm to cluster joints and faults. …”
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An Automatic Generalization Method of a Block-Based Digital Depth Model Based on Surface Curvature Features by Dong Wang, Jian Dong, Lulu Tang, Mengkai Ma, Tian Xie

“…Initially, a clustering blocking model is established using an improved K-means algorithm for partitioning DDM data. Subsequently, a fitting surface is constructed based on the neighboring depth points within the blocked DDM to obtain the surface curvature characteristics of each depth point, which serve as the criterion for the DDM automatic generalization process. …”
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