K-means clustering of a soil sampling scheme with data on the morphography of the Ogosta valley northwestern Bulgaria by Assen TCHORBADJIEFF, Tsvetan KOTSEV, Velimira STOYANOVA, Emilia TCHERKEZOVA

“…The field sites are split into 4 clusters using K-means algorithm with the following variables: elevation, distance to the river, vertical distance to channel network, multiresolution index of valley bottom flatness and a modified topographic SAGA wetness index. …”
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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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Three-Dimensional Aerodynamic Optimization of Single-Layer Reticulated Cylindrical Roofs Subjected to Mean Wind Loads by Bingbing San, Chen Xu, Ye Qiu

“…The aim of this paper is to determine the best performing rise-to-span ratio of cylindrical roofs based on the gradient algorithm. Two objective functions were considered to minimize the highest mean suction on the roof surface and the maximum response displacement of the single-layer reticulated cylindrical shell subjected to mean wind loads. …”
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PCA-counseled k-means and k-medoids with dimension reduction for improved in determining optimal aid clustering by Achmad Jauhari, Ika Oktavia Suzanti, Devie Rosa Anamisa, Fadhila Tangguh Admojo

“…This analysis shows thatPCA-k-means is an effective technique for creating accurate and unique clusters withina data set's structure.The clustering results using the PCA-k-means algorithm have produced the greatest accuracy in the silhouette score of 0.49 and the DBI score is 0.84. …”
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Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs by Jie Yu, Linqi Zhu, Ruibao Qin, Zhansong Zhang, Li Li, Tao Huang

“…However, due to the weak correlation between the logging response of coalbed methane reservoirs and the gas content parameters and strong nonlinear characteristics, it is difficult for conventional gas content calculation algorithms to obtain more reliable results. This paper proposes a CBM reservoir gas content assessment method combining K-means clustering and random forest. …”
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Assessment of air purifiers for improving the air quality index using circular intuitionistic fuzzy Heronian means by Fengyu Guo, Raiha Imran, Shi Yin, Kifayat Ullah, Maria Akram, Dragan Pamucar, Mustafa Elashiry

“…So, considering this, the Heronian mean (HM) operator and its special cases such as averaging and geometric operators have been used in this paper. …”
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Time Series Clustering Analysis for Increases Food Commodity Prices in Indonesia Based on K-Means Method by M. Fariz Fadillah Mardianto, N. Ramadhan Al Akhwal Siregar, Steven Soewignjo, F. Friska Rahmana Putri, Hadi Prayogi, Citra Imama, Dita Amelia, . Sediono, Deshinta Arrova Dewi

“…The clustering algorithm employs the K-Means method, necessitating a comprehensive description of the groups it forms. …”
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A comparison of various imputation algorithms for missing data. by Jürgen Kampf, Iryna Dykun, Tienush Rassaf, Amir Abbas Mahabadi

“…Among the remaining algorithms, in most situations we tested, predictive mean matching performed best.…”
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Assessing the Effect of Water on Submerged and Floating Plastic Detection Using Remote Sensing and K-Means Clustering by Lenka Fronkova, Ralph P. Brayne, Joseph W. Ribeiro, Martin Cliffen, Francesco Beccari, James H. W. Arnott

“…Spectral analysis was conducted to assess the attenuation of individual wavelengths of the submerged tarpaulin in UAV hyperspectral and Sentinel-2 multispectral data. A K-Means unsupervised clustering algorithm was used to classify the images into two clusters: plastic and water. …”
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Hybridization of DEBOHID with ENN algorithm for highly imbalanced datasets by Sedat Korkmaz

“…Machine learning algorithms assume that datasets are balanced, but most of the datasets in the real world are imbalanced. …”
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Utilizing Statistical Tests for Comparing Machine Learning Algorithms by Hozan Khalid Hamarashid

“…To conduct whether or not the mean result differences between two algorithms is genuine then statistical hypothesis test is utilized. …”
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PV Power Short-Term Forecasting Method Based on VMD-GWO-ELMAN by Na ZHANG, Qiang REN, Guangchen LIU, Liping GUO, Jingyu LI

Subjects: “…k-means cluster…”
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Transmission Line Anomaly Detection and Real-Time Monitoring System Combining Edge Computing and EfficientDet by Menghao Lin, Yang Ding, Tianle Wang, Yang Liu, Zewei Li

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Convex Optimization and PV Inverter Control Strategy-Based Research on Active Distribution Networks by Jiachuan Shi, Sining Hu, Rao Fu, Quan Zhang

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Image denoising algorithm based on multi-channel GAN by Hongyan WANG, Xiao YANG, Yanchao JIANG, Zumin WANG

“…Aiming at the issue that the noise generated during image acquisition and transmission would degrade the ability of subsequent image processing, a generative adversarial network (GAN) based multi-channel image denoising algorithm was developed.The noisy color image could be separated into red-green-blue (RGB) three channels via the proposed approach, and then the denoising could be implemented in each channel on the basis of an end-to-end trainable GAN with the same architecture.The generator module of GAN was constructed based on the U-net derivative network and residual blocks such that the high-level feature information could be extracted effectively via referring to the low-level feature information to avoid the loss of the detail information.In the meantime, the discriminator module could be demonstrated on the basis of fully convolutional neural network such that the pixel-level classification could be achieved to improve the discrimination accuracy.Besides, in order to improve the denoising ability and retain the image detail as much as possible, the composite loss function could be depicted by the illustrated denoising network based on the following three loss measures, adversarial loss, visual perception loss, and mean square error (MSE).Finally, the resultant three-channel output information could be fused by exploiting the arithmetic mean method to obtain the final denoised image.Compared with the state-of-the-art algorithms, experimental results show that the proposed algorithm can remove the image noise effectively and restore the original image details considerably.…”
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Prediction Algorithm of Parameters of Toe Clearance in the Swing Phase by Tamon Miyake, Masakatsu G. Fujie, Shigeki Sugano

“…Moreover, using gait data of other five subjects, the root mean square error between the true and predicted values was 4.04 mm for the maximum toe clearance and 2.88 mm for the minimum toe clearance when the walking velocity changed. …”
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Optimum Median Filter Based on Crow Optimization Algorithm by Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim al-Aqbi, Lamees abdalhasan Salman

“…It achieves the simulation based on MATLAB R2019b and the results present that the improved median filter with crow optimization algorithm is more effective than the original median filter algorithm and some recently methods; they show that the suggested process is robust to reduce the error problem and remove noise because of a candidate of the median filter; the results will show by the minimized mean square error to equal or less than (1.38), absolute error to equal or less than (0.22) ,Structural Similarity (SSIM) to equal (0.9856) and getting PSNR more than (46 dB). …”
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Efficient model-and-data based channel estimation algorithm by Kai MEI, Haitao ZHAO, Xiaoran LIU, Jun LIU, Jun XIONG, Baoquan REN, Jibo WEI

“…For orthogonal frequency division multiplexing (OFDM) systems, a hybrid model and data driven channel estimation algorithm was proposed.Combined with two existing channel estimation methods, including a low complex learning-based channel estimation method and the linear minimum mean square error (LMMSE) channel estimation, the estimator with the ability was facilitated to employ online training to improve estimation performance.Meanwhile, the pilot overhead consumed by generating online training data was saved due to the use of the model-based method in the proposed algorithm, which improved the spectrum efficiency.The simulation results demonstrate that the proposed algorithm has better performance under low signal-to-noise ratio (SNR) and better adaptation to practical imperfections compared with conventional channel estimation methods.…”
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Study of the ternary correlation quantum-behaved PSO algorithm by Tao WU, Xi CHEN, Yu-song YAN

“…The novel algorithm changed the information independent ran-dom processing method of standard QPSO and established internal relations during particles' own experience information, group sharing information and the distance from the particles' current location to the population mean best position using normal copula functions.Then, the method of generating ternary correlation factors was given by using the Cholesky square root formula. …”
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Efficient model-and-data based channel estimation algorithm by Kai MEI, Haitao ZHAO, Xiaoran LIU, Jun LIU, Jun XIONG, Baoquan REN, Jibo WEI

“…For orthogonal frequency division multiplexing (OFDM) systems, a hybrid model and data driven channel estimation algorithm was proposed.Combined with two existing channel estimation methods, including a low complex learning-based channel estimation method and the linear minimum mean square error (LMMSE) channel estimation, the estimator with the ability was facilitated to employ online training to improve estimation performance.Meanwhile, the pilot overhead consumed by generating online training data was saved due to the use of the model-based method in the proposed algorithm, which improved the spectrum efficiency.The simulation results demonstrate that the proposed algorithm has better performance under low signal-to-noise ratio (SNR) and better adaptation to practical imperfections compared with conventional channel estimation methods.…”
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