Seed multispectral imaging combined with machine learning algorithms for distinguishing different varieties of lettuce (Lactuca sativa L.) by Jinpeng Wei, Zhangyan Dai, Qi Zhang, Le Yang, Zhaoqi Zeng, Yuliang Zhou, Jun Liu, Bingxian Chen

“…Then we applied Support Vector Machine (SVM), Random Forest (RF), and Back-Propagation Neural Network (BP), Linear Discriminant Analysis (LDA) for variety identification. …”
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Fault reconfiguration control strategy of islanded marine ranching power supply system based on deep reinforcement learning by Yichun Wang, Bo Zhang, Rongjie Wang, Jiang Desong, Yabo Cui, Zhouyang Sun, Hao Liu

“…To enhance convergence efficiency and generalization capability of the algorithm, noise networks are used to improve exploration ability of dueling DQN algorithm by implementing linear layers with learnable noise using an adaptive noise model. …”
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…LR struggles with class imbalance due to its linear assumptions and bias toward the majority class, while GNB’s reliance on feature independence and Gaussian distribution make it unreliable for under-represented minority classes. …”
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Kinetics of Sludge Superheated Steam Drying and Optimization of Process Parameters by Xukun Zhang, Pu Xing, Shengping Liu, Chengzhen Zhang, Weiliang Fu

“…The quadratic polynomials, linear equation, and logarithmic model can better fit the change law of water variation of the sludge of superheated steam condensation section, recovery section, and drying section. …”
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Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

“…Our findings showed that the multiple linear regression is the most effective model in predicting biomass while artificial neural networks showed up as the top performing algorithm in determining nitrogen content. …”
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Inactivation Kinetics of <i>Escherichia coli</i> and <i>Staphylococcus aureus</i> Using Ultrasound in a Model Parenteral Emulsion by Maricarmen Iñiguez-Moreno, Montserrat Calderón-Santoyo, Gabriel Ascanio, Estefanía Brito-Bazán, María Soledad Córdova-Aguilar, Edmundo Brito-de la Fuente, Juan Arturo Ragazzo-Sánchez

“…The Weibull model provided the best fit, highlighting the non-linear nature of microbial inactivation. The US presents a promising alternative for microbial control in food and pharmaceutical applications. …”
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An FPGA-Based SiNW-FET Biosensing System for Real-Time Viral Detection: Hardware Amplification and 1D CNN for Adaptive Noise Reduction by Ahmed Hadded, Mossaad Ben Ayed, Shaya A. Alshaya

“…This integration of SiNW-FET with FPGA-based CNN noise reduction offers a unique approach, as prior noise reduction techniques for biosensors typically rely on linear filtering or digital smoothing, which lack adaptive capabilities for complex, non-linear noise patterns. …”
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Human genotype-to-phenotype predictions: Boosting accuracy with nonlinear models. by Aleksandr Medvedev, Satyarth Mishra Sharma, Evgenii Tsatsorin, Elena Nabieva, Dmitry Yarotsky

“…First, we ask if state-of-the-art nonlinear predictive models, such as boosted decision trees, can be more efficient for phenotype prediction than conventional linear models. …”
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Synthesis of a Biglucoside and Its Application as Montmorillonite Hydration Inhibitor by Xin-chun Zhang, Xing-zhi Wang, Gang Chen, Qiang Deng, Huarui Hao

“…Under the same condition, the linear expansion ratio of montmorillonite in BG solution is much lower than that of MEG. …”
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Comparing Machine Learning Algorithms to Enhance Volumetric Water Content Prediction in Low-Cost Soil Moisture Sensor by Iman Setiawan, Mohammad Dahlan Th. Musa, Dini Aprilia Afriza, Siti Nur Hafidah

“…The results suggested that KNN (0.02939128) had the smallest RMSE value followed by decision tree (0.05144186) and linear regression model (0.05172371).…”
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A New Modification of the Reconstruction of Variational Iteration Method for Solving Multi-order Fractional Differential Equations by E. Hesameddini, A. Rahimi

“…For that reason, we need a reliable and efficient technique for the solution of fractional differential equations. …”
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Physical Modeling of Core Losses in Ferrite E-Cores by Theophane Dimier, Jurgen Biela

“…This method combines an analytical solution of the field in the core with a non-linear material model of ferrite, modelling all relevant loss phenomena such as hysteresis losses and non-linear resonant eddy currents. …”
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Least-squares Smoothed Shape Functions for Constructing Field-Consistent Timoshenko Beam Elements by Foek Tjong Wong, Henokh G. Tjahyono, Sugiyono Hartono, Timothy A. Setiabudi

“…These elements are then applied to linear static analysis, bifurcation buckling analysis, and free vibration analysis of prismatic and tapered beams. …”
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Nonlinear System Identification of Folding Fins with Freeplay Using Direct Parameter Estimation by Zhi-Sai Ma, Bo Wang, Xin Zhang, Qian Ding

“…Experimental results demonstrate that the proposed method is able to decouple the linear and nonlinear dynamics of a nonlinear structure and estimate natural frequencies of the derived linear system along with nonlinear internal forces in one computational step, even if no a priori knowledge of the type of nonlinearities is given.…”
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Computational Reconstruction of the Volatility Term Structure in the General Hull–White Model by Slavi G. Georgiev, Lubin G. Vulkov

“…We computationally recover the volatility term structure as a piecewise-linear function of time. For every maturity, a cost functional, defined as the squared differences between theoretical and market prices, is minimized and the respective linear part is reconstructed. …”
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Estimation of parameters for 3D geomechanical modeling from triaxial test results by Artem Kukhtinskii

“…A Python script is developed to automate the calculation of elastic modulus and Poisson's ratio, overcoming subjectivity in selecting the linear portion of stress-strain curves. The script optimally identifies the linear region by minimizing the fit error with appropriate constraints, ensuring a more objective and standardized approach. …”
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Local appearance-based face recognition using adaptive directional wavelet transform by Mohd. Abdul Muqeet, Raghunath S. Holambe

“…The latest research has shown that adaptive directional wavelet transform can constitute edges and textures in images efficiently due to the adaptive directional selectivity. …”
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A Modal-Based Substructure Method Applied to Nonlinear Rotordynamic Systems by Helmut J. Holl

“…Modal analysis is performed for each linear and symmetric background system of the substructure. …”
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High-Resolution Squinted SAR Imaging Algorithm Applied in the Near-Field Environment by Shijia Wang, Shibo Wang, Wanli Liu

“…In the squinted synthetic aperture radar (SAR) imaging of the near-field environment, range-dependent characteristic of squint angle cannot be ignored, which causes azimuth-dependent range cell migration (RCM) after linear range walk correction (LRWC). In this study, an efficient SAR imaging algorithm applied in the near-field environment is proposed. …”
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Flexibility provision by virtual power line and soft open point in AC/DC distribution systems by Xiaodong Yang, Wentao Jiang, Jing Ma, Da Xu, Chengjia Zhang, Yue Yang, Zhicheng Xu

“…To address the voltage quality and operational efficiency issues caused by the high penetration of PVG, this paper fully explores the regulation potential of hybrid AC/DC distribution networks (HDNs) and electric vehicles (EVs). …”
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