Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

“…Finally, PAM is introduced into the above established model for realizing the desired deterministic and probabilistic predictions where the relationship among the wind speed data recorded at various time intervals and the data variability are considered. …”
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Advanced reference crop evapotranspiration prediction: a novel framework combining neural nets, bee optimization algorithm, and mode decomposition by Ahmed Elbeltagi, Okan Mert Katipoğlu, Veysi Kartal, Ali Danandeh Mehr, Sabri Berhail, Elsayed Ahmed Elsadek

“…In this context, our study aimed to enhance the accuracy of ETo prediction models by combining a variety of signal decomposition techniques with an Artificial Bee Colony (ABC)–artificial neural network (ANN) (codename: ABC–ANN). …”
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Optimizing Vehicle Scheduling Based on Variable Timetable by Benders-and-Price Approach by Zekang Lan, Shiwei He, Rui Song, Sijia Hao

“…A Benders-and-Price algorithm by combining the Benders decomposition and column generation is proposed to solve the LP-relaxation of the path-based model, and a bespoke Branch-and-Price is used to obtain the integer solution. …”
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The effect of macroeconomic variables on non performance financing of Islamic Banks in Indonesia by Latifah Dian Iriani, Imamudin Yuliadi

“…Research methodology used at this study is Vector Error Correction Model (VECM). Following these procedures, it applies Unit Roots Test, Augmented Dickey Fuller Test, Lag Length Criteria Test, Correlation Matrix – Johansen Julius Co-integration Test, VECM Estimation, Impulse Response and Variance Decomposition Test. …”
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The effect of macroeconomic variables on non performance financing of Islamic Banks in Indonesia by Latifah Dian Iriani, Imamudin Yuliadi

“…Research methodology used at this study is Vector Error Correction Model (VECM). Following these procedures, it applies Unit Roots Test, Augmented Dickey Fuller Test, Lag Length Criteria Test, Correlation Matrix – Johansen Julius Co-integration Test, VECM Estimation, Impulse Response and Variance Decomposition Test. …”
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Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours by Hua Deng, Kai Zhou

“…Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. …”
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Advancing the Reliability of Future Hydrological Projections in a Snow‐Dominated Alpine Watershed: Integrating Uncertainty Decomposition and CycleGAN Bias Correction by Tao Su, Zhu Liu, Qingyun Duan, Xinwei Mao, Weidong Xu

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Numerical investigation of mixed convection and viscous dissipation in couple stress nanofluid flow: A merged Adomian decomposition method and Mohand transform by Khader Mohamed M., Adel Mohamed, Messaoudi Mohamed

“…The research focuses on how these variables impact the model’s overall heat transfer characteristics and the fluid’s behavior. …”
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What explains differences in average wait time in the emergency department among different racial and ethnic populations: A linear decomposition approach by Hao Wang, Nethra Sambamoorthi, Richard D. Robinson, Heidi Knowles, Jessica J. Kirby, Amy F. Ho, Trevor Takami, Usha Sambamoorthi

“…The extent to which demographic, clinical, and hospital factors explained the differences in average wait time among the three groups were analyzed with Blinder‒Oaxaca post‐linear decomposition model. Results There were 310,253 total patients including 34.7% of NHW, 34.7% of NHB, and 30.6% of Hispanic patients. …”
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Variability in the volume transport of deep overflow across the 10°S saddle on the ninetyeast ridge by Shanwu Zhang, Fuwen Qiu, Hangyu Chen, Chunsheng Jing

“…These variabilities are attributed to vertically propagating Rossby waves originating from wind stress curl-induced Ekman pumping, which is demonstrated via spectral empirical orthogonal function decomposition of numerical model outputs and by ray tracing based on the dispersion relation for baroclinic Rossby waves. …”
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Impact of Phase Angle Jump on a Doubly Fed Induction Generator under Low-Voltage Ride-Through Based on Transfer Function Decomposition by Peiru Feng, Jiayin Xu, Zhuang Wang, Shenghu Li, Yuming Shen, Xu Gui

“…Firstly, the differential-algebraic equations of the DFIG are linearized to propose their transfer function model. Secondly, considering its high-order characteristic, a model reduction method for the transfer function of the DFIG using the Schur decomposition is proposed, and the analytical expression of the output variables of the DFIG with the phase angle jump is derived by the inverse Laplace transformation to judge the necessity of the LVRT measures. …”
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Finding quadratic underestimators for optimal value functions of nonconvex all-quadratic problems via copositive optimization by Markus Gabl, Immanuel M. Bomze

“…Modeling parts of an optimization problem as an optimal value function that depends on a top-level decision variable is a regular occurrence in optimization and an essential ingredient for methods such as Benders Decomposition. …”
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Spatial distribution and urban–rural disparity of unmet need for family planning among married/in-union women in Ethiopia: a spatial and decomposition analysis by Shimels Derso Kebede, Daniel Niguse Mamo, Jibril Bashir Adem, Agmasie Damtew Walle, Yawkal Tsega, Elsabeth Addisu, Zinabu Bekele Tadese, Ermias Bekele Enyew

“…Finally, multivariable decomposition analysis via a logit model was used to decompose the observed difference in unmet need by the compositional difference and the difference in effects of explanatory variables between places of residence.ResultsSpatial distribution of unmet need for family planning was clustered in Ethiopia with a global Moran's I index value of 0.25 (p-value = 0.004). …”
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Decomposing social groups differential in stunting among children under five in India using nationally representative sample data by Mriganka Dolui, Sanjit Sarkar

“…Descriptive statistics, multivariable logistic regression, F-test, t-test and chi-squared (χ²) test were applied to understand the prevalence, determinants, and associations, respectively. The Fairlie decomposition model was applied to quantify the factors contributing to the inequality of stunting across social groups. …”
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Modeling the relationship among the stock market, gold price, oil price and exchange rate: A VECM and VDA approach by Agrawal Pravin Kumar, Kumar Mohit

“…By employing a Vector Error Correction Model (VECM) and Variance Decomposition Analysis (VDA), the study explores both the short-term and long-term dynamics between these asset classes. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

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An Artificial Intelligence-Based Approach With Photoplethysmogram and Heart Rate Variability for Sleep Bruxism Diagnosis by Omer Eris, Mehmet Recep Bozkurt, Seval Bulut Eris, Cahit Bilgin

“…The models were optimized and tested using unseen data. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To address these limitations, this study employs the covariance matrix decomposition method to generate 3D lognormal random fields for soil parameters, enabling efficient modeling of spatial variability. …”
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Hyperbolic extensions of constrained PDEs by Fernando Abalos, Oscar Reula, David Hilditch

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Real-time prediction of port water levels based on EMD-PSO-RBFNN by Lijun Wang, Shenghao Liao, Sisi Wang, Jianchuan Yin, Ronghui Li, Jingyu Guan

“…Addressing the spatial variability, temporal dynamics, and non-linearity characteristics of port water levels, a hybrid prediction scheme was proposed, which integrates empirical mode decomposition (EMD) with a radial basis function neural network (RBFNN), optimized using the particle swarm optimization (PSO) algorithm. …”
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