Vertiport Infrastructure Location Optimization for Equitable Access to Urban Air Mobility by Vasileios Volakakis, Hani S. Mahmassani

“…An Agglomerative Hierarchical Clustering (AHC) model was utilized for the identification of candidate vertiport locations, along with a k-means algorithm, for comparison and validation purposes, based on an estimated UAM demand pattern. …”
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A Decision Support System for Classifying Suppliers Based on Machine Learning Techniques: A Case Study in the Aeronautics Industry by Ana Claudia Andrade Ferreira, Alexandre Ferreira de Pinho, Matheus Brendon Francisco, Laercio Almeida de Siqueira, Guilherme Augusto Vilas Boas Vasconcelos

“…The proposed methodology is important for both industry and academia, as it helps managers make decisions about the quality of their suppliers and compares the use of four different algorithms for this purpose, which is an important insight for new studies. The K-Means algorithm obtained the best performance both for the metrics obtained and the simplicity of use. …”
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Two-stage Community Discovery Algorithm for Multi-point Seed Prepartition by TONG Shuai, CHEN De-yun, YANG Hai-lu

“…First，high-impact nodes in the network are identified，and high-impact nodes are aggregated using the k-means algorithm to obtain high-impact community clusters. …”
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Analysis and Identification of Students with Financial Difficulties: A Behavioural Feature Perspective by Yong Ma, Xingxu Zhang, Xiaoqiang Di, Tao Ren, Huamin Yang, Binbin Cai

“…Finally, we adopted the semisupervised K-means algorithm to more accurately find out students with financial difficulties. …”
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Segmentation of Striatal Brain Structures from High Resolution PET Images by Ricardo J. P. C. Farinha, Ulla Ruotsalainen, Jussi Hirvonen, Lauri Tuominen, Jarmo Hietala, José M. Fonseca, Jussi Tohka

“…The weighted kernel k-means algorithm is used to partition the graph describing the voxel affinities within the striatum into the desired number of clusters. …”
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Clustering‐based recommendation method with enhanced grasshopper optimisation algorithm by Zihao Zhao, Yingchun Xia, Wenjun Xu, Hui Yu, Shuai Yang, Cheng Chen, Xiaohui Yuan, Xiaobo Zhou, Qingyong Wang, Lichuan Gu

“…By combining the K‐means algorithm with the enhanced GOA, which incorporates a Lévy flight mechanism and multi‐strategy co‐evolution, our method overcomes the centroid sensitivity issue, a key limitation in traditional clustering techniques. …”
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A typical scenario generation method for renewable energy power systems based on time-sequenced operational simulations by PENG Zhuyi, SONG Shan, XU Sixuan, GU Kanghui, GE Yi, WANG Quanquan, SUN Wentao

“…Secondly， based on data characteristics such as renewable energy output levels， line congestion conditions， and unit startup-shutoff from the time-sequenced simulation results， an improved K-means algorithm is employed to extract typical scenarios. …”
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Segmentation of Energy Consumption Using K-Means: Applications in Tariffing, Outlier Detection, and Demand Prediction in Non-Smart Metering Systems by Darío Muyulema-Masaquiza, Manuel Ayala-Chauvin

“…This research assesses the efficacy of the K-Means algorithm when applied to the monthly billing records of 221,401 residential customers from Empresa Eléctrica Ambato Regional Centro Norte S.A. …”
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Kinematics of Supernova Remnants Using Multiepoch Maximum Likelihood Estimation: Chandra Observation of Cassiopeia A as an Example by Yusuke Sakai, Shinya Yamada, Toshiki Sato, Ryota Hayakawa, Nao Kominato

“…To investigate asymmetric structures, such as singular components that deviate from the direction of expansion, the MLE method was extended to combine multiple computational domains and classify kinematic properties using the k -means algorithm. This approach allowed for the mapping of different physical states onto the image, and one classified component was suggested to interact with circumstellar material by comparison with infrared observations from the James Webb Space Telescope. …”
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Optimizing Solar Energy Harvesting: A K‐Means Clustering Approach for Enhanced Efficiency and Viability by Li Bin, Muhammad Shahzad, Muhammad Farhan, Muhammad Sanaullah Khan, Mubaarak Abdulrahman Abdu Saif, Girmaw Teshager Bitew

“…This research introduces an innovative synthesis method for a typical solar radiation year (TSRY) based on K‐means clustering to maximize energy harvest. The K‐means algorithm, a fundamental image processing technique, is utilized to classify images into distinct groups. …”
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m-QAM Receiver Based on Data Stream Spectral Clustering for Optical Channels Dominated by Nonlinear Phase Noise by Miguel Solarte-Sanchez, David Marquez-Viloria, Andrés E. Castro-Ospina, Erick Reyes-Vera, Neil Guerrero-Gonzalez, Juan Botero-Valencia

“…We demonstrate that the spectral clustering algorithm outperforms the k-means algorithm in the face of nonlinear phase noise in −90, −100, and −110 dBc/Hz scenarios at 1 MHz in a simulated 10 GHz symbol rate channel.…”
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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin Ab Rahman, Sakib Iqram Hamim

“…This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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A Decentralized Fuzzy C-Means-Based Energy-Efficient Routing Protocol for Wireless Sensor Networks by Osama Moh’d Alia

“…In this initial construction step, a fuzzy C-means algorithm is adopted to allocate sensor nodes into their most appropriate clusters. …”
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Cheetah optimized CNN: A bio-inspired neural network for automated diabetic retinopathy detection by V. K. U. Ahamed Gani, N. Shanmugasundaram

“…The segmented output is clustered using the cascaded fuzzy C-means algorithm and features are extracted with the speeded-up robust features algorithm. …”
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Are Labour Markets Segmented in Developing Economies? A Clustering Approach for Colombian Workers by David Arturo Rodriguez Guerrero, Jorge Eliecer Quintero

“…Using the FAMD-K-means algorithm we find three clusters: one comprises half the workforce, has workers with secondary education or vocational training, without labour contracts, and median earnings slightly above the minimum wage. …”
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Piezoelectric Active Sensor Self-Diagnosis for Electromechanical Impedance Monitoring Using K-Means Clustering Analysis and Artificial Neural Network by Xie Jiang, Xin Zhang, Yuxiang Zhang

“…And the damage information represented by PCs was clustered by the K-means algorithm to identify the cases of damage. Then, the degrees of sensor damages were classified with the artificial neural network (ANN). …”
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Analysis of global stock market development-Integration of clustering, classification, and shapley values. by Marcin Stawarz

“…The research applies the K-means algorithm for clustering, which enables the segmentation of exchanges based on their similarities. …”
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Water distribution from medium-size sprinkler in solid set sprinkler systems by Giuliani do Prado

“…The sixteen water distribution curves were normalized and subjected to clustering analysis (K-Means algorithm), identifying the occurrence of normalized distribution curves with three different geometric shapes. …”
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Gender Identification Using Multilayer Perceptron (MLP) Neural Network, Genetic Neural Network and Adaptive Neuro-Fuzzy Inference System (ANFIS) Network by Evanthia Kokkinaki

“…The most optimal outcome was achieved through the integration of the ANFIS network with the Fuzzy C-Means algorithm. Furthermore, alternative approaches proved to be highly efficacious. …”
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Electric Vehicle Charging Load Forecasting Based on K-Means++-GRU-KSVR by Renxue Shang, Yongjun Ma

“…To address this issue, this paper proposes a regional forecasting method based on K-means++ clustering and deep learning algorithms. First, the K-means++ algorithm was used to partition the data into different regions, and an independent load-forecasting model was established for each region. …”
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