NON HIERARCHICAL K-MEANS ANALYSIS TO CLUSTERING PRIORITY DISTRIBUTION OF FUEL SUBSIDIES IN INDONESIA by Ani Budi Astuti, Abdi Negara Guci, Viky Iqbal Azizul Alim, Laila Nur Azizah, Meirida Karisma Putri, Wigbertus Ngabu

“…Therefore, there is a need for appropriate action from the government in determining related policies. K-Means multivariate cluster analysis is a non-hierarchical cluster method that is popularly used, one of which is used in Machine Learning algorithms, especially Unsupervised Learning. …”
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SAR Images Change Detection Based on Attention Mechanism-Convolutional Wavelet Neural Network by Jiahui E, Lu Wang, Chunhui Zhao, P. Takis Mathiopoulos, Tomoaki Ohtsuki, Fumiyuki Adachi

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Multi-Objective Cluster Classification and Voltage Control Approach for Active Distribution Network Considering Resource Reserve Degree by Jing WANG, Yi YUAN, Yinchi SHAO, Jinqi ZHANG, Ran DING, Yanjiang GONG

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Improvement in panchromatic-guided denoising algorithm for research on Beijing SDGSAT-1 luminous remote sensing image denoising algorithm by Lihan Zhang, Linyan Bai, Ruren Li, Jianzhong Feng, Penglong Wang, Chao Chen

“…In this study, based on existing denoising algorithms, the OTSU threshold method is combined with a convolution window to identify noisy pixels. …”
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Positive Anchor Area Merge Algorithm: A Knowledge Distillation Algorithm for Fruit Detection Tasks Based on Yolov8 by Xiangqun Shi, Xian Zhang, Yifan Su, Xun Zhang

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Vibe++ background segmentation method combining MeanShift clustering analysis and convolutional neural network by Zihao LIU, Xiaojun JIA, Sulan ZHANG, Zhiling XU, Jun ZHANG

“…To solve problems of noise points and high segmentation error for image shadow brought by traditional Vibe+ algorithm, a novel background segmentation method (Vibe++) based on the improved Vibe+ was proposed.Firstly, binarization image was acquired by using traditional Vibe+ algorithm from surveillance video.The connected regions were marked based on the region-growing domain marker method.The area threshold was obtained with difference characteristics of boundary area, the connected regions below threshold were treated as disturbing points.Secondly, five different kernel functions were introduced to improve the traditional MeanShift clustering algorithm.After improving, this algorithm was fused effectively with partitioned convolutional neural network.Finally, program of classification of trailing area, non-trailing area and trailing edge area in the resulting image was performed.Position coordinates of the trailing area were calculated and confirmed, and the trailing area was quickly deleted to obtain the final segmentation result.This segmentation accuracy was greatly improved by using the proposed method.The experimental results show that the proposed algorithm can achieve segmentation accuracy of more than 98% and has good application effect and high practical value.…”
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Monitored Reconstruction: Computed Tomography as an Anytime Algorithm by Konstantin Bulatov, Marina Chukalina, Alexey Buzmakov, Dmitry Nikolaev, Vladimir V. Arlazarov

“…Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. …”
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Optimasi Algoritma Naive Bayes dengan Diskritisasi K-Means pada Diagnosis Penyakit Jantung by Nafa Fajriati, Budi Prasetiyo

“…K-means discretization changes the value of each continuous attribute into discrete categories in the form of k clusters formed from the K-means algorithm process. …”
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Hybrid Genetic Algorithm with Filters to Image Enhancement by Baydaa Bhnam

“…The new suggested algorithm <strong>HGAF</strong> uses popular (mean , median and min-max filters) and other proposed filters as fitness function for it in order to design eight proposed genetic filters. …”
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Balanced Cluster Head Selection Based on Modified -Means in a Distributed Wireless Sensor Network by Sasikumar Periyasamy, Sibaram Khara, Shankar Thangavelu

“…The results show that Mk- means (modified k -means) algorithm was found to outperform the existing clustering algorithms owing to its unique multiple cluster head methodology.…”
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A Novel Algorithm in the Management of Hypoglycemia in Newborns by Swapna Naveen, Chikati Rosy, Hemasree Kandraju, Deepak Sharma, Tejopratap Oleti, Srinivas Murki

“…Conclusion. A new and novel algorithm in the management of hypoglycemia in neonates is as safe as the standard protocol and requires further testing before routine implementation.…”
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Fusion spectrum sensing algorithm based on eigenvalues by Wenjing ZHAO, He LI, Minglu JIN

“…Aiming at the problem of inefficient use of spectrum resources,a fusion spectrum sensing algorithm based on eigenvalues was proposed to effectively achieve dynamic spectrum sharing.The test statistics were constructed by employing the maximum eigenvalue,the trace and the geometric mean of all eigenvalues of the sample covariance matrix.The detection probability and false alarm probability of the proposed method were analyzed using the random matrix theory,and the analytical representation of the theoretical threshold was obtained.In addition,the parameter selection of the proposed algorithm was analyzed theoretically.Simulation results show that the proposed algorithm has better detection ability than the existing eigenvalue detection algorithm.…”
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Hybrid genetic algorithm based optimization of pilotpattern by Hanbing ZHENG, Xiang YU, Weiwei WANG

“…In OFDM system,sparse channel estimation based on compressed sensing(CS)can make full use of the inherent sparse degree of the wireless channel,which can reduce the pilot overhead and improve the spectrum efficiency.Therefore,a new method based on hybrid genetic algorithm was investigated for the pilot design of CS channel estimation,which was based on the minimization of the matrix cross correlation in the CS theory.In this method,genetic algorithm was used to obtain the initial sub-optimal pilot sequence,and then combined with the pilot position and pilot power,each entry of pilot pattern could be sequentially updated and optimized to make the minimum correlation of measurement matrix.Simulation results show that the proposed method can ensure a better mean square error and bit error rate compared to the pseudo-random pilot design and the equal distance pilot design.…”
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Nonlinear Gossip Algorithms for Wireless Sensor Networks by Chao Shi, Yuanshi Zheng, Hongbing Qiu, Junyi Wang

“…By using Lyapunov theory, Lagrange mean value theorem, and stochastic Lasalle’s invariance principle, we prove that the nonlinear single gossip algorithms can converge to the average of initial states with probability one. …”
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Technique for target recognition based on intuitionistic fuzzy c-means clustering and kernel matching pursuit by Yang LEI, Wei-wei KONG, Ying-jie LEI

“…Kernel matching pursuit requires every step of searching process be global optimal searching in the redundant dictionary of function.Namely,the dictionary learning time of KMP was too long.To the above drawbacks,a novel technique for KMP based on IFCM was proposed to substitute local searching for global searching by the property superiority of dynamic clustering performance,which was also the superiority in Intuitionistic fuzzy c-means algorithm.Then two testing including classification and effectiveness were carried out towards four real sample data.Subsequently,high resolution range profile (HRRP)was selected from the classical properties of target recognition in e middle ballistic trajectory,which were extracted for getting sub-range profile.Finally,three algorithms including FCM,KMP,IFCM-KMP were carried out respectively towards different kinds of sub-range profile samples in emulation platform,the conclusion of which fully demonstrates that the IFCM-KMP algorithm is superior over FCM and KMP when it comes to target recognition in the middle ballistic trajectory.…”
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Automatic Leak Detection in Buried Plastic Pipes of Water Supply Networks by Means of Vibration Measurements by Alberto Martini, Marco Troncossi, Alessandro Rivola

“…The experimental campaign is here described and discussed. The proposed algorithm, enhanced by means of proper signal filtering techniques, was successfully tested on all monitored leaks, thus proving effective for leak detection purpose.…”
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Research on Credit Card Default Prediction Based on k-Means SMOTE and BP Neural Network by Ying Chen, Ruirui Zhang

“…Aiming at the problem that the credit card default data of a financial institution is unbalanced, which leads to unsatisfactory prediction results, this paper proposes a prediction model based on k-means SMOTE and BP neural network. In this model, k-means SMOTE algorithm is used to change the data distribution, and then the importance of data features is calculated by using random forest, and then it is substituted into the initial weights of BP neural network for prediction. …”
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Application of the Mean-shift Segmentation Parameters Estimator (MSPE) to VHSR satellite images: Tetuan-Morocco by O. Benarchid, N. Raissouni, J.A. Sobrino, A. El Ayyan

“…MSPE estimates the parameters values for the Mean-shift Segmentation (MS) algorithm. However, this algorithm needs as inputs: i) existing vector database and, ii) spectral data to define automatically the segmentation parameter values. …”
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A Multi-Objective Particle Swarm Optimization Approach for Optimizing K-Means Clustering Centroids by Aina Latifa Riyana Putri, Joko Riyono, Christina Eni Pujiastuti, Supriyadi

“…The K-Means algorithm is a popular unsupervised learning method used for data clustering. …”
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Research on Particle Filter Video Tracking Algorithms by YU Shuchun, TONG Xiaoyu

“…Aiming at the problem of insufficient robustness of moving target tracking in complex scenes, a particle filter target tracking algorithm based on CNN feature extraction is proposed CNN selflearning mechanism is used to extract highlevel semantic features of objects in images Chaotic sequence variable scale firefly algorithm is introduced to improve the accuracy of target recognition A particle filter tracking algorithm combining mean shift and weight optimization is constructed to optimize the weight of particles, improve the diversity of particle sets and make video tracking more accurate The simulation results show that the proposed algorithm can effectively adapt to occlusion, illumination, violent motion and other scenes, and has good adaptability and high realtime performance to illumination change, scale change, occlusion and so on The results of comparison with seven other methods show that under the same experimental conditions, the tracking success rate and tracking accuracy of this method are 5%~40% higher than those of other methods…”
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