Generalized Preconditioned MHSS Method for a Class of Complex Symmetric Linear Systems by Cui-Xia Li, Yan-Jun Liang, Shi-Liang Wu

“…Numerical experiments are reported to confirm the efficiency of the proposed methods.…”
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An Unbiased Convex Estimator Depending on Prior Information for the Classical Linear Regression Model by Mustafa I. Alheety, HM Nayem, B. M. Golam Kibria

“…We propose an unbiased restricted estimator that leverages prior information to enhance estimation efficiency for the linear regression model. The statistical properties of the proposed estimator are rigorously examined, highlighting its superiority over several existing methods. …”
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Quasi-Linear Convective Systems in Catalonia Detected Through Radar and Lightning Data by Tomeu Rigo, Carme Farnell

“…Quasi-Linear Convective Systems (QLCSs) are a type of Mesoscale Convective System characterised by their linear shape and association with severe weather phenomena (such as hail, tornadoes, or wind gusts). …”
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Polypropylene blends: Impact of long chain-branched polypropylene on crystallization of linear polypropylene by Soňa Zenzingerová, Jana Navratilova, Lenka Gajzlerová, Michal Kudláček, David Jaška, Lubomir Benicek, Roman Čermák

“…This study compares the efficiency of commercially available sorbitol-based clarifying agent (NA) and varying amounts of long chain-branched polypropylene (LCBPP) acting as a specific α-nucleating agent for linear polypropylene (PP). …”
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Variational Bayesian EM Algorithm for Quantile Regression in Linear Mixed Effects Models by Weixian Wang, Maozai Tian

“…This paper extends the normal-beta prime (NBP) prior to Bayesian quantile regression in linear mixed effects models and conducts Bayesian variable selection for the fixed effects of the model. …”
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Synchronization Analysis for Stochastic Inertial Memristor-Based Neural Networks with Linear Coupling by Lixia Ye, Yonghui Xia, Jin-liang Yan, Haidong Liu

“…This paper concerns the synchronization problem for a class of stochastic memristive neural networks with inertial term, linear coupling, and time-varying delay. Based on the interval parametric uncertainty theory, the stochastic inertial memristor-based neural networks (IMNNs for short) with linear coupling are transformed to a stochastic interval parametric uncertain system. …”
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Predicting Market Value of Iranian Football Players using Linear Modeling Techniques by Rasool Nazari, Saeid Azari

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Cons-training tensor networks: Embedding and optimization over discrete linear constraints by Javier Lopez-Piqueres, Jing Chen

“…These tensor networks are particularly tailored for modeling distributions with support strictly over the feasible space, offering benefits such as reducing the search space in optimization problems, alleviating overfitting, improving training efficiency, and decreasing model size. Central to our approach is the concept of a quantum region, an extension of quantum numbers traditionally used in $U(1)$ symmetric tensor networks, adapted to capture any linear constraint, including the unconstrained scenario. …”
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Newton-Kantorovich Method for Solving One of the Non-Linear Sturm-Liouville Problems by Hussien A. H. Abugirda, Khaldoun S. Al-Yasiri, Mohammed Kh. Abdullah

“…Also, to show the efficiency of applying this method to solve these problems, a comparison is made in this paper between the Newton-Kantorovich method and the Adomian decomposition method applied to the same non-linear Sturm-Liouville problems under consideration in this work. …”
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Spectrum Allocation Using Integer Linear Programming and Kerr Optical Frequency Combs by Sergio Muñoz-Tapasco, Andrés F. Calvo-Salcedo, Jose A. Jaramillo-Villegas

“…Spectrum allocation methods, such as the Routing, Modulation Level, and Spectrum Assignment (RMLSA) approach, play a crucial role in executing this strategy efficiently. While current algorithms have improved allocation efficiency, further development is necessary to optimize network performance. …”
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Comparison of Linear and Nonlinear Features of Electroencephalogram to Classify Alcoholic and Non-Alcoholic People by Elizabeth Stewart, Owen Kelly

“…The present study intends to use various types of linear and nonlinear analysis of the EEG signal to classify alcoholics and non-alcoholics and provide a direct comparison of the efficiency of each of the analysis methods. …”
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Unsupervised feature selection based on generalized regression model with linear discriminant constraints by Xiangguang Dai, Mingyu Guan, Facheng Dai, Wei Zhang, Tingji Zhang, Hangjun Che, Xiangqin Dai

“…Abstract Unsupervised feature selection (UFS) methods play a crucial role in improving the efficiency of extracting relevant information and reducing computational complexity in the context of big data analysis. …”
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A review of finite control set model predictive control for linear machines by Wei Xu, Han Xiao, Yirong Tang, Jian Ge, Leilei Guo, Abdul Khalique Junejo

“…Among the numerous control methods of LM drive systems, finite control set model predictive control (FCS‐MPC) method has been given special attention due to its clear concept, fast response performance, and ability to handle constrained multivariate non‐linear control problems. It is widely used to improve the performance and efficiency of overall LM drive systems. …”
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Improving SVM performance through data reduction and misclassification analysis with linear programming by Carlos Aníbal Suárez, Mauricio Castro, Mariuxi Leon, Carlos Martin-Barreiro, Michael Liut

“…Therefore, removing data points is equivalent to reducing the dimensionality of the dual problem, leading to a more efficient optimization process. We introduce linear programming models to determine whether two sets of points are linearly separable efficiently, compute the misclassification rate, and reduce the dimension of the optimization problems behind the SVM procedure. …”
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PARALLEL APPROACH TO SOLVE OF THE DIRECT SOLUTION OF LARGE SPARSE SYSTEMS OF LINEAR EQUATIONS by Michal Bošanský, Bořek Patzák

“…The paper deals with parallel approach for the numerical solution of large, sparse, non-symmetric systems of linear equations, that can be part of any finite element software. …”
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Linear Time Train Contraction Minor Labeling for Railway Line Capacity Analysis by Qinglun Zhong, Ruihua Xu

“…The proposed method based on train contraction minor contributes to the railway operations community by promoting the efficient computation of railway line capacity into linear time.…”
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Experimental study on the performance of concrete linear cutting by high pressure water jet by Lan Zhang, Jingyan Lu, Haitao Li, Bo Li

“…The results of the study deepen the understanding of the characteristics of high-pressure water jet linear cutting concrete, and lay a theoretical foundation for the selection of parameters for efficient breaking of concrete by water jet.…”
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Comparison of Gaussian Elimination and Cholesky Decomposition Solving A Linear System Of Equation. by Nzabonimpa, Godfrey

“…There are several methods of solving a system of linear equations. Some of which are direct methods and others are iterative methods. …”
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Controller Design for Continuous-Time Linear Control Systems with Time-Varying Delay by Hongli Yang, Lijuan Yang, Ivan Ganchev Ivanov

“…The derived conditions are formulated as linear matrix inequalities (LMIs) that become affine upon fixing a single scalar parameter, thereby facilitating efficient numerical computation. …”
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Symbolic regression modelling of the linear growth rates of stationary cross-flow instabilities by Lucas Pascal

“…Additionally, tests conducted on a three-dimensional (3-D) prolate spheroid show strong alignment with transition lines computed by means of exact linear stability. Overall, this model provides a practical and efficient alternative for accurately predicting cross-flow transitions in complex 3-D geometries, contributing to improved aerodynamic design and analysis.…”
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