Construction control of cable-stayed bridge top push method based on BIM technology by Chengyong Chen, Wenming Su, Wenqiang Dou, Yongquan Dong, Ben Zhang

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Borrowing in modern Russian language: related linguistic processes by Natalia V. Gabdreeva, Anastasia V. Ageeva

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Bearing Fault Diagnosis Method Based on Improved VMD and Parallel Hybrid Neural Network by Wuyi Chen, Huafeng Cai, Qiu Sun

“…In order to combat the difficulty of fault feature extraction and fault recognition in the field of bearing fault diagnosis, a bearing fault diagnosis method based on improved variational mode decomposition (VMD) and parallel hybrid neural network is proposed, which combines reweighted kurtosis (RK) with variable mode decomposition (VMD) and uses reweighted kurtosis as the evaluation index to select the decomposition times of variational mode decomposition, while removing part of the interference in the fault signal and retaining its impact characteristics. …”
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Formulating genome‐scale kinetic models in the post‐genome era by Neema Jamshidi, Bernhard Ø Palsson

“…We describe here a framework for building and analyzing such models. The mathematical analysis challenges are reflected in four foundational properties, (i) the decomposition of the Jacobian matrix into chemical, kinetic and thermodynamic information, (ii) the structural similarity between the stoichiometric matrix and the transpose of the gradient matrix, (iii) the duality transformations enabling either fluxes or concentrations to serve as the independent variables and (iv) the timescale hierarchy in biological networks. …”
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Estimation of heat transfer parameters by using trained POD-RBF and Grey Wolf Optimizer by Minh Ngoc Nguyen, Nha Thanh Nguyen, Thien Tich Truong

“…In order to accelerate the process, the model order reduction technique Proper-Orthogonal-Decomposition (POD) is used. …”
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A novel data processing approach to detect fraudulent insurance claims for physical damage to cars by Ahmet Yücel

“…To this end, Singular Value Decomposition-based components and correlation-based composite variables were created. …”
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Ultra-Short-Term Photovoltaic Power Prediction Based on Predictable Component Reconstruction and Spatiotemporal Heterogeneous Graph Neural Networks by Yingjie Liu, Mao Yang

“…A circuit singular spectral decomposition (CISSD) intrinsic predictable component extraction method is adopted to obtain specific frequency components in sensitive meteorological variables, a mechanism based on radiation characteristics and PV power trend predictable component extraction and reconstruction is proposed to enhance power predictability, and a spatiotemporal heterogeneous graph neural network (STHGNN) combined with a Non-stationary Transformer (Ns-Transformer) combination architecture to achieve joint prediction for different PV components. …”
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A Simple and Effective KAN-Based Architecture for Accurate Battery RUL Prediction by Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen, Shufei Li

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Short-Term Wind Speed Prediction Using EEMD-LSSVM Model by Aiqing Kang, Qingxiong Tan, Xiaohui Yuan, Xiaohui Lei, Yanbin Yuan

“…Partial autocorrelation function is adopted to analyze the inner relationships between the historical wind speed series in order to determine input variables of LSSVM models for prediction of every subseries. …”
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Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…The model offers a solution to the challenge of accurately predicting generated solar PV power while considering the dynamic nature of environmental variables and solar radiation variability. …”
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House Prices and the Effectiveness of Monetary Policy in an Estimated DSGE Model of Morocco by Roubyou Said, Ouakil Hicham

“…Bayesian estimation over the period 2007Q2–2017Q2 of a dynamic stochastic general equilibrium model allowed us to reveal a significant impact of the increase in policy interest rates on the prices of residential goods. …”
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Modeling deforestation drivers in the Brazilian Amazon: a comparison of quantitative approaches by Alisson Castro Barreto, Tailon Martins, Adriano Mendonça Souza

“…In contrast, the BVAR model demonstrated superior performance by effectively modeling lagged effects and feedback loops among variables. …”
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Inadequacies in the representation of sub-seasonal phytoplankton dynamics in Earth system models by M. G. Keerthi, M. G. Keerthi, O. Aumont, L. Kwiatkowski, M. Levy

“…<p>Sub-seasonal phytoplankton dynamics on timescales between 8 d and 3 months significantly contribute to annual fluctuations, making it essential to accurately represent this variability in ocean models to avoid distorting long-term trends. …”
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Global, regional, and national burden of endocrine, metabolic, blood, and immune disorders from 1990 to 2021, and projections to 2050: a systematic analysis of the global burden of... by Jinpai Liang, Hongyan Leng, Xuelian Bai, Linling Li, Tao Qin, Jiazhi Ruan, Guoxing Wang, Wenjuan Zhang

“…Bayesian age-period-cohort (BAPC) models were applied for projections to 2050. Decomposition analysis attributed changes in disease burden to population growth, aging, and epidemiological shifts.ResultsIn 2021, the global incidence of EMBID was 79.47 million (95% UI 63.34–98.63 million), with an age-standardized rate of 957.58 (95% UI 766.99–1,183.95) per 100,000, showing a slight decline (EAPC: -0.24% [95% CI -0.35 – -0.12]). …”
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Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

“…This paper investigates carbon emissions in Zhejiang Province. First, the variable mode decomposition method is used to decompose the historical data of carbon emissions in Zhejiang Province, enabling an analysis of its cyclicality fluctuations. …”
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The linkage between oil price, stock market indices, and exchange rate before, during, and after COVID-19: Empirical insights of Pakistan by Mosab I. Tabash, Zaheeruddin Babar, Umaid A Sheikh, Ather Azim Khan, Suhaib Anagreh

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A Marketing Capability Based Export Performance Model for IRAN Software Market by Shahriar Azizi, Vahid Makizadeh, Behtash Jamalieh Bastami

“…Identification of factors affecting export performance of software developers can improve planning that in turn results in increasing software export. In this research a model consisting of seven important variables in software industries including: competitive intensity, marketing planning and executing capability along with three market orientation factors (customer and competition orientation and inter-functional coordination) proposed. …”
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Data-Driven Model Predictive Control for Trajectory Tracking in UAV-Manipulator Systems by Bryan S. Guevara, Jose Varela-Aldas, Viviana Moya, Manuel Cardona, Daniel C. Gandolfo, Juan M. Toibero

“…Real-world data was collected using the Matrice 100 platform and Dynamixel MX-28AR actuators to identify a high-dimensional linear model via Dynamic Mode Decomposition with Control (DMDc), capturing the interactions between the aerial vehicle and the manipulator across 21 state variables. …”
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Model Optimization for High-Yield Biocrude in Co-Hydrothermal Liquefaction of Municipal Sludge by Botian HAO, Yunfei DIAO, Ya WEI, Donghai XU

“…The Box-Behnken Design (BBD) was used to develop a three-factor, three-level response surface model, selecting reaction temperature (280 - 340 ℃), residence time (15 - 45 min), and biomass-to-water mass ratio (1∶5 - 1∶15) as key variables. …”
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Random Finite Element Analysis and Random Factor response Mechanism for Geocell-reinforced Soil Retaining Walls by ZHANG Bingbing, SONG Fei

“…For this reason, a finite element analysis method based on random field theory is proposed in this paper, which can more realistically reflect the non-homogeneous characteristics of the reinforced soil retaining wall system by introducing a spatial random distribution model of the soil parameters and the mechanical properties of the geocells, so as to more accurately assess the influence of the spatial variability of the material parameters on the deformation behavior and stability of the retaining wall.MethodsFirstly, in parameter random field modeling, an innovative combination of Latin Hypercube Sampling (LHS) and exponential autocorrelation function is used to construct parameter random fields. …”
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