Identification of Anomaly Detection in Power System State Estimation Based on Fuzzy C-Means Algorithm by Di Leng, Ziliang Qiu

“…An anomaly detection identification method based on fuzzy C-means algorithm is proposed to cluster the measured data and identify the anomaly detection of power system. …”
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An improved incremental least-mean-squares algorithm for distributed estimation over wireless sensor networks by Mou Wu, Liansheng Tan, Rong Yang, Runze Wan

“…Thereby we propose an improved incremental least-mean-squares distributed estimation algorithm that starts from the incremental least-mean-squares algorithm and works toward the objective of improvement on initial convergence rate and steady-state performance. …”
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Improving Performance of Cluster Heads Selection in DEC Protocol Using K-Means Algorithm for WSN by Abdulla Juwaied, Lidia Jackowska-Strumillo

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eFC-Evolving Fuzzy Classifier with Incremental Clustering Algorithm Based on Samples Mean Value by Emmanuel Tavares, Gray Farias Moita, Alisson Marques Silva

“…Starting its knowledge base from scratch, the eFC structure evolves based on a clustering algorithm that can add, merge, delete, or update clusters (= rules) simultaneously while providing class predictions. …”
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Optimization of Human Resource Performance Management System Based on Improved R-Means Clustering Algorithm by Rui Wang

“…An improved R-means clustering algorithm and a clustering analysis model based on R-means clustering algorithm are proposed, and the corresponding algorithm flow and implementation are given.…”
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Sedimentary Environment Analysis by Grain-Size Data Based on Mini Batch K-Means Algorithm by Qiao Su, Yanhui Zhu, Yalin Jia, Ping Li, Fang Hu, Xingyong Xu

“…Furthermore, we will use the Mini Batch K-means algorithm with the most appropriate parameters (reassignment ratio ϵ=0.025 and mini batch = 25) to cluster the sediment samples. …”
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K-Gen PhishGuard: an Ensemble Approach for Phishing Detection with K-Means and Genetic Algorithm by Ali Al-Hafiz, Adnan Jabir, Shamala Subramaniam

Subjects: “…AdaBoost; ensemble learning; feature selection; genetic algorithm; K-means clustering; machine learning; phishing detection…”
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A Bridge Crack Segmentation Algorithm Based on Fuzzy C-Means Clustering and Feature Fusion by Yadong Yao, Yurui Zhang, Zai Liu, Heming Yuan

“…In response to the limitations of traditional image processing algorithms, such as high noise sensitivity and threshold dependency in bridge crack detection, and the extensive labeled data requirements of deep learning methods, this study proposes a novel crack segmentation algorithm based on fuzzy C-means (FCM) clustering and multi-feature fusion. …”
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3D WSN clustering routing algorithm based on IHBA optimized fuzzy C-means by Jing YANG, Biyang XU, Weizheng LI, Wei LI, Zhaoqiang ZHU, Tao QIN

Subjects: “…3D wireless sensor network;clustering routing;honey badger algorithm;fuzzy C-means;energy consumption balance…”
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Symbol timing recovery algorithm based on ordered statistic of maximum mean power timing for WBAN by HIYu C, HENLan C, VChao L

“…The symbol timing algorithm based on maximum mean power timing is independent of carrier phase offset,and has the property of capturing timing information fast,which meets the demand of wireless body area networks (WBAN).According to IEEE 802.15.6 standard,the ordered statistic of maximum mean power timing was used to reduce the computational complexity in the symbol timing process.The theoretical analysis and simulation results shows that the proposed algorithm can achieve symbol timing within 32 symbols and reduce the computational complexity by ninety percent at most compared to the original maximum mean power algorithm.The fast synchronization and car-rier-independence property of the proposed algorithm can also make room for carrier-offset recovery and frame synchro-nization.…”
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A Distributed Weighted Possibilistic c-Means Algorithm for Clustering Incomplete Big Sensor Data by Qingchen Zhang, Zhikui Chen

“…Possibilistic c-means clustering algorithm (PCM) has emerged as an important technique for pattern recognition and data analysis. …”
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Method for Solving Large Linear Algebraic Equation Systems Based on Kaczmarz–K-Means Algorithm by Hao Li

“…In response to the problems in solving large-scale linear algebraic equations, this study adopts two block discrimination criteria, the Euclidean clustering and the cosine clustering, to decompose them into row vectors and construct the K-means clustering algorithm. Based on the uniformly distributed block Kaczmarz algorithm, the weight coefficients are integrated into the probability criterion to construct a new and efficient weight probability. …”
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Optimizing K-Means Algorithm Using the Purity Method for Clustering Oil Palm Producing Regions by Novia Hasdyna, Rozzi Kesuma Dinata, Balqis Yafis

Subjects: “…k-means algorithm…”
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Detection of <i>Aspergillus flavus</i> in Figs by Means of Hyperspectral Images and Deep Learning Algorithms by Cristian Cruz-Carrasco, Josefa Díaz-Álvarez, Francisco Chávez de la O, Abel Sánchez-Venegas, Juan Villegas Cortez

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Theoretical knowledge enhanced genetic algorithm for mine ventilation system optimization considering main fan adjustment by Wentian Shang, Jinzhang Jia

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Machine learning classification algorithm screening for the main controlling factors of heavy oil CO2 huff and puff by Peng-xiang Diwu, Beichen Zhao, Hangxiangpan Wang, Chao Wen, Siwei Nie, Wenjing Wei, A-qiao Li, Jingjie Xu, Fengyuan Zhang

Subjects: “…Classification algorithm…”
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Dimensionality Reduction using Hybrid Algorithms and Their Application to Remote Sensing Data by Maha Hasso, Mona Siddiq

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Novel algorithm of maintaining packet order in two-stage switch by ZHANG Xiao-ning, XU Du, LI Le-min

“…However, in its basic fabric, the load-balanced switch may mis-sequence the packets. A new algorithm called FFS （full frame stuff） was proposed in this paper, which maintains packet order in the two-stage load-balanced switch and has excellent switching performance （in terms of mean delay and throughput）.This algorithm is distributed and each port operates independently.…”
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Research on Gearbox Fault Diagnosis based on Improved LMD Algorithm by Haibo Xing, Yue Chen, Jinghao Li

“…Aiming at the fault diagnosis of gearbox，an Improved Local Mean Decomposition （ILMD） algorithm is proposed and applied to the extraction of fault features of gearbox. …”
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Diversity and multiplexing based on GMD algorithm by HE Zhong-tang1, AI Ju-mei2, HU Luo-quan1, ZHANG Li-jun1

Subjects: “…multiple input multiple output;geometric mean decomposition algorithm;outage probability;sigular value decomposition;diversity and multiplexing…”
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