Evaluation of Cluster Algorithms for Radar-Based Object Recognition in Autonomous and Assisted Driving by Daniel Carvalho de Ramos, Lucas Reksua Ferreira, Max Mauro Dias Santos, Evandro Leonardo Silva Teixeira, Leopoldo Rideki Yoshioka, João Francisco Justo, Asad Waqar Malik

“…Our analysis covered a variety of current methods, the mathematical process of these methods, and presented a comparison table between these algorithms, including Hierarchical Clustering, Affinity Propagation Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Mini-Batch K-Means, K-Means Mean Shift, OPTICS, Spectral Clustering, and Gaussian Mixture. …”
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Fractional time delay estimation algorithm based on the fractional lower order moment by LIU Wen-hong1, 2, QIU Tian-shuang1, HU Ting-ting1, LUAN Lian-yi3

“…According to the noise characteristics in signal, a fractional time delay estimation algorithm referred to as LMPFTDE was proposed based on the least mean p-norm. …”
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Online blind equalization algorithm with echo state network based on prediction principle by Ling YANG, Qin HAN, Li CHENG, Aonan ZHAO, Juan DU

“…In view of the nonlinear channel,the online blind equalization algorithm with echo state network was proposed based on prediction principle.In the proposed algorithm,the traditional linear prediction error filter was replaced by the ESN with good nonlinear mapping ability,and recursive least square (RLS) algorithm was used to calculate the output weight of the network to minimize the network prediction error.Then,the amplitude and phase were adjusted.Simulation results show that the proposed algorithm can effectively reduce the distortion caused by nonlinear channel to the transmitted signal for 16QAM signal,which has lower mean square error and faster convergence speed in comparison with other blind equalization algorithms based on prediction principle.…”
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Fractional time delay estimation algorithm based on the fractional lower order moment by LIU Wen-hong1, 2, QIU Tian-shuang1, HU Ting-ting1, LUAN Lian-yi3

“…According to the noise characteristics in signal, a fractional time delay estimation algorithm referred to as LMPFTDE was proposed based on the least mean p-norm. …”
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Online blind equalization algorithm with echo state network based on prediction principle by Ling YANG, Qin HAN, Li CHENG, Aonan ZHAO, Juan DU

“…In view of the nonlinear channel,the online blind equalization algorithm with echo state network was proposed based on prediction principle.In the proposed algorithm,the traditional linear prediction error filter was replaced by the ESN with good nonlinear mapping ability,and recursive least square (RLS) algorithm was used to calculate the output weight of the network to minimize the network prediction error.Then,the amplitude and phase were adjusted.Simulation results show that the proposed algorithm can effectively reduce the distortion caused by nonlinear channel to the transmitted signal for 16QAM signal,which has lower mean square error and faster convergence speed in comparison with other blind equalization algorithms based on prediction principle.…”
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Characterization of microbiota signatures in Iberian pig strains using machine learning algorithms by Lamiae Azouggagh, Noelia Ibáñez-Escriche, Marina Martínez-Álvaro, Luis Varona, Joaquim Casellas, Sara Negro, Cristina Casto-Rebollo

“…ML models exploring maternal, paternal and heterosis effects showed varying levels of classification performance, with the paternal effect scenario being the best, achieving a mean Area Under the ROC curve (AUROC) of 0.74 using the Catboost (CB) algorithm. …”
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Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest by Murad Ibrahim Husin Alzawali, Yusliza Yusoff, Razana Alwee, Zuriahati Mohd Yunos, Mohamad Shukor Talib, Haswadi Hassan, Fahad Taha AL-Dhief, Musatafa Abbas Abbood Albadr, Majid Razaq Mohamed Alsemawi, Sharifah Zarith Rahmah Syed Ahmad

“…In addition, the Binarized Genetic Algorithm (BGA) is utilized as a features selection in order to select the most effective features of HOG. …”
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Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm by Yuanwen Lai, Hangyu Liang, Liling Huang

“…The model is trained and tested by using bus operation data. The root mean square error of the Kalman filter model is 0.351, of the BP neural network model is 0.059, and of the FA-BP prediction model is 0.04. …”
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Optimization of algorithms transferring numeric positional codes for discrete channels with the fluctuation noise by Sergey Gennad'yevich Rassomahin, Oleg Pavlovich Malofey, Aleksandr Olegovich Malofey

“…The article suggests algorithm for generating and processing signals for transmission of positional codes, based on the criterion of minimum mean squared error recovery numbers on the output channel with additive white Gaussian noise (AWGN). …”
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The Artificial Bee Colony (ABC) Algorithm for Estimating Parameter of Epidemic Influenza Model by Agus Suryanto, Syaiful Anam

“…The Artificial Bee Colony (ABC) is one of the stochastic algorithms that can be applied to solve many real-world optimization problems. …”
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ESTIMATION ALGORITHM OF WEAR RATE ON TOOTH SURFACE AT CIRCULAR HELICAL-GEAR BREAKING-IN by Artem Yuryevich Lukonin

“…In the process of gearing breaking-in, teeth are worn down. The estimation algorithm of such wear rate in the circular helical point gearing is described. …”
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Idiographic Lapse Prediction With State Space Modeling: Algorithm Development and Validation Study by Eric Pulick, John Curtin, Yonatan Mintz

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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

“…Accordingly, in this study, a differential evolution algorithm (DEA) is hybridized with an electromagnetism-like algorithm (EMA) in the mutation stage to enhance the reliability and efficiency of the DEA. …”
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Variable Selection Algorithm for Explaining Anomalies in Real-World Regenerative Thermal Oxidizers by Min-Ji Seo, Myung-Ho Kim

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Compressed sensing subspace pursuit algorithm based on two stagewise weak selection by Bowei WANG, Jin TAN

“…Compressed sensing is a new way of signal sampling and data compression.The subspace pursuit algorithm has higher efficiency and precision in the compressed sensing reconstruction algorithms,but it needs the sparsity of the signal as a priori information.And if the sparsity estimation is not accurate enough,it will reduce the algorithm reconstruction effect.Aiming at this problem,a two stagewise weak selection-based subspace pursuit (TSWSP) algorithm was proposed,which didn’t need to know the sparsity of the signal in advance.The first weak selection adaptively selected the initial atom candidate set,and the second weak selection adaptively culled the wrong atoms that may had been previously selected from the current atom support set,and finally it selected a plurality of related atoms from the current atom candidate set to join the atom support set by the backtracking method.Simulation analysis shows that the proposed algorithm can reconstruct one-dimensional random signals and two-dimensional image signals accurately with unknown sparsity,and it has high stability,compared with OMP,SWOMP,BAOMP,SAMP and SP algorithm,the mean-square erroris reduced by 60.5% to 99.1%,the peak signal-to-noise ratio is improved by 2.1% to 34.3%.…”
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Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm by Methaq Hadi Lafta

“…So this research is trying to provide a method based on LQG controller with and then set motion and specify path scheduling without deviations based on swarm intelligence algorithms in combinational mode: Dragonfly-Firefly algorithm. …”
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Robust Recursive Algorithm under Uncertainties via Worst-Case SINR Maximization by Xin Song, Feng Wang, Jinkuan Wang, Jingguo Ren

“…It demonstrates that our proposed recursive algorithm provides excellent robustness against signal steering vector mismatches and the small training data size and, has fast convergence rate, and makes the mean output array signal-to-interference-plus-noise ratio (SINR) consistently close to the optimal one. …”
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An improved YOLOv5n algorithm for detecting surface defects in industrial components by Jia-Hui Tian, Xue-Feng Feng, Feng Li, Qing-Long Xian, Zhen-Hong Jia, Jie-Liang Liu

“…Experimental results demonstrate that the improved YOLOv5n algorithm achieves a mean average precision of 75.3% on the NEU-DET dataset, which is 4.3% higher than the original model.…”
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Deep Belief Network-Based Multifeature Fusion Music Classification Algorithm and Simulation by Tianzhuo Gong

“…In this paper, the multifeature fusion music classification algorithm and its simulation results are studied by deep confidence networks, the multifeature fusion music database is established and preprocessed, and then features are extracted. …”
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Pothole Detection and Assessment on Highways Using Enhanced YOLO Algorithm With Attention Mechanisms by Rufus Rubin, Chinnu Jacob, Sumod Sundar, Gabriel Stoian, Daniela Danciulescu, Jude Hemanth

“…It enhances detection by modifying the YOLO algorithm, using the Xception backbone, and integrating attention mechanisms to improve the prediction of small or clustered objects. …”
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