Penerapan Metode K-Means Berbasis Jarak untuk Deteksi Kendaraan Bergerak by Yuslena Sari, Andreyan Rizky Baskara, Puguh Budi Prakoso

“…In this paper, the K-Means algorithm applies Euclidean distance, Manhattan distance, Canberra distance, Chebyshev distance and Braycurtis distance. …”
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Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model by Chuansheng Zhang, Minglai Yang

“…Ablation experiment results show that introducing K-means clustering improves the model’s running speed, while the improved QPSO algorithm and the introduction of multiple kernel functions enhance the model’s accuracy. …”
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K-Means Based Bee Colony Optimization for Clustering in Heterogeneous Sensor Network by Prince Modey, Gaddafi Abdul-Salaam, Emmanuel Freeman, Patrick Acheampong, William Leslie Brown-Acquaye, Israel Edem Agbehadji, Richard C. Millham

“…This study proposes a Bee Colony Optimization that synergistically combines K-mean algorithms (referred to as K-BCO) for efficient clustering in heterogeneous sensor networks. …”
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Substructure correlation adaptation transfer learning method based on K-means clustering by Haoshuang LIU, Yong ZHANG, Yingbo CAO

“…Domain drifts severely affect the performance of traditional machine learning methods, and existing domain adaptive methods are mainly represented by adaptive adjustment cross-domain through global, class-level, or sample-level distribution adaptation.However, too coarse global matching and class-level matching can lead to insufficient adaptation, and sample-level adaptation to noise can lead to excessive adaptation.A substructure correlation adaptation (SCOAD) transfer learning algorithm based on K-means clustering was proposed.Firstly, multiple subdomains of the source domain and the target domain were obtained by K-means clustering.Then, the matching of the second-order statistics of the subdomain center was sought.Finally, the target domain samples were classified by using the subdomain structure.The proposed method approach further improves the performance of knowledge transfer between the source and target domains on top of the traditional approach.Experimental results on common transfer learning datasets show the effectiveness of the proposed method.…”
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Substructure correlation adaptation transfer learning method based on K-means clustering by Haoshuang LIU, Yong ZHANG, Yingbo CAO

“…Domain drifts severely affect the performance of traditional machine learning methods, and existing domain adaptive methods are mainly represented by adaptive adjustment cross-domain through global, class-level, or sample-level distribution adaptation.However, too coarse global matching and class-level matching can lead to insufficient adaptation, and sample-level adaptation to noise can lead to excessive adaptation.A substructure correlation adaptation (SCOAD) transfer learning algorithm based on K-means clustering was proposed.Firstly, multiple subdomains of the source domain and the target domain were obtained by K-means clustering.Then, the matching of the second-order statistics of the subdomain center was sought.Finally, the target domain samples were classified by using the subdomain structure.The proposed method approach further improves the performance of knowledge transfer between the source and target domains on top of the traditional approach.Experimental results on common transfer learning datasets show the effectiveness of the proposed method.…”
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Prediction of Sound Insulation of Sandwich Partition Panels by Means of Artificial Neural Networks by Naveen GARG, Siddharth DHRUW, Laghu GANDHI

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Passenger Flow Prediction of Integrated Passenger Terminal Based on K-Means–GRNN by Yifan Tan, Haixu Liu, Yun Pu, Xuemei Wu, Yubo Jiao

“…In this paper, the passenger flow GRNN prediction model is proposed, based on the K-means cluster algorithm, and an improved index named BWPs (Between-Within Proportion-Similarity) is proposed to improve the clustering effect of K-means so that the clustering effect of the new index is verified. …”
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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. …”
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Robotic constructor as a means of teaching C++ programming to high school students by Anton V. Eliseev

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High frequency radar error classification and prediction based on K-means methods by Zhaoyi Wang, Zhaoyi Wang, Marie Drevillon, Pierre De Mey-Frémaux, Elisabeth Remy, Nadia Ayoub, Dakui Wang, Bruno Levier

“…This study aims to characterize the high frequency radar and numerically simulated low-frequency filtered currents in the south-eastern Bay of Biscay (study area) using a K-means classification algorithm based on an improved Euclidean Distance calculation method that does not take missing values. …”
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Development of biometric systems for passenger identification based on noise-resistant coding means by A. A. Gladkikh, A. K. Volkov, T. G. Ulasyuk

“…The problem to minimize memory amount for the permutation decoder cognitive map due to the permutation orbits allocation and usage of the generated loops combinations as pointers of reference plane is solved. The resulting algorithm for finding a unique orbit number and its corresponding reference plane by means of receiver formation of arbitrary parameters permutation from the set of permissible permutations is proposed.…”
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Deep learning based automation of mean linear intercept quantification in COPD research by Lars Leyendecker, Anna Louisa Weltin, Florian Nienhaus, Michaela Matthey, Bastian Nießing, Daniela Wenzel, Daniela Wenzel, Robert H. Schmitt, Robert H. Schmitt

“…The extent of airspace enlargement that is characteristic for emphysema is quantified by manual assessment of the mean linear intercept (MLI) across multiple histological microscopy images. …”
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Secure K-Means Clustering Scheme for Confidential Data Based on Paillier Cryptosystem by Zhengqi Zhang, Zixin Xiong, Jun Ye

“…In this paper, we propose a secure homomorphic K-means clustering protocol based on the Paillier cryptosystem to address the urgent need for privacy-preserving clustering techniques in sensitive domains such as healthcare and finance. …”
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Evaluation of geological engineering factors for productivity of deep CBM well after fracturing based on grey correlation method by KONG Xiangwei,XIE Xin,WANG Cunwu,SHI Xian

Subjects: “…|coal-bed methane|grey correlation method|fracturing effect|k-means clustering algorithm|optimization of fracturing parameters…”
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Computational Aspects of <i>L</i>₀ Linking in the Rasch Model by Alexander Robitzsch

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Wind power generation prediction using LSTM model optimized by sparrow search algorithm and firefly algorithm by Wenjing Zhang, Hongjing Yan, Lili Xiang, Linling Shao

“…To raise the accuracy of wind power generation prediction, a bidirectional long short-term memory network combination model based on sparrow search algorithm and firefly algorithm optimization is designed. …”
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Threshold Analysis of Request Degradation in the Computer Network by Vasilii P. Kirnos

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Intelligent recognition algorithm of connection relation of substation secondary wiring drawing based on D-LLE algorithm by Hongzhi Liu, Bojie Yang, Fang Kang, Qian Li, Hongyang Zhang

“…The experimental results show that the completeness of connection information extraction of substation secondary wiring drawings obtained by the proposed algorithm is between 98.56% and 99.98%, and the mean absolute error of intelligent recognition drawings connection relationship is always lower than 0.01. …”
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Multipath Estimation of Navigation Signals Based on Extended Kalman Filter–Genetic Algorithm Particle Filter Algorithm by Jie Li, Xiyan Sun, Yuanfa Ji, Jingjing Li, Long Li

“…The particle filter (PF) algorithm has found widespread application in navigation multipath estimation. …”
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Optimization Management of Storage Location in Stereoscopic Warehouse by Integrating Genetic Algorithm and Particle Swarm Optimization Algorithm by Shuhong Zhang, Xianghui Zheng, Fan Xu, Suzhen Wang, Qixia Zhang, Yuan Cao

“…At the same time, the study introduced the GA-PSO algorithm to solve the mathematical model and optimize the goods location planning. …”
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