An Improved Wavelet Soft-Threshold Function Integrated with SVMD Dual-Parameter Joint Denoising for Ancient Building Deformation Monitoring by Jiaxing Zhao, Houzeng Han, Yang Deng, Youqiang Dong, Jian Wang, Wenjin Chen

“…This study integrates sequential variational mode decomposition (SVMD), a dual-parameter (DP) model, and an improved wavelet threshold function (IWT), presenting a denoising method termed SVMD-DP-IWT. …”
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A Hybrid Model for Carbon Price Forecasting Based on Secondary Decomposition and Weight Optimization by Yongfa Chen, Yingjie Zhu, Jie Wang, Meng Li

“…To further alleviate mode mixing in the high-frequency components, an improved variational mode decomposition (VMD) optimized by particle swarm optimization (PSO) is applied for secondary decomposition. …”
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Optimised Neural Network Model for Wind Turbine DFIG Converter Fault Diagnosis by Ramesh Kumar Behara, Akshay Kumar Saha

“…This research introduces an enhanced fault detection approach, variational mode decomposition (VMD), for identifying open-circuit IGBT faults in the grid-side converter (GSC) of a doubly fed induction generator (DFIG) wind turbine system. …”
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Monolithic and Decomposition Methods for Optimal Scheduling of Dynamically Adaptive Water Networks by Bradley Jenks, Aly-Joy Ulusoy, Ivan Stoianov

“…We compare the performance of a decomposition method using the alternating direction method of multipliers (ADMM) with a gradient-based sequential convex programming (SCP) monolithic solver. …”
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A multi-modal feature combination mechanism for identification of harmonic load in distribution networks based on artificial intelligence models by Renzeng Yang, Shuang Peng, Gang Yao

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Electricity pinch analysis method for flexibility supply-demand matching in power systems by Yaling Mao, Tiejiang Yuan, Xueqin Tian, Yue Teng

“…First, the net-load profile is decomposed by successive variational mode decomposition (SVMD) optimized with the Red-billed Blue Magpie Optimization (RBMO) algorithm to construct a flexibility demand model. …”
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Evaluation of variation of salt dust hygroscopic aerosol particle size as a function of relative air humidity by Konstantin A. Chernyi, Grigorii Z. Faynburg

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Temporal and interanimal variation in bloodspot acylcarnitine and amino acid profiles in relation to conventional metabolites and hormones in Holstein dairy cows by Pius Lutakome, Stijn Heirbaut, Muluken Mulat Girma, Mingqi Zhang, Xiaoping Jing, Karolien Hertogs, Katleen Geerinckx, Els Stevens, Ben Aernouts, Leen Vandaele, Denis Asizua, Fred Kabi, Veerle Fievez

“…To gain deeper understanding of these mechanisms, we evaluated changes in bloodspot acylcarnitines (AC) and free AA profiles, and conventional blood biomarkers of energy balance (BHB, nonesterified fatty acids [NEFA], glucose, insulin, IGF-1, and fructosamine) along with weekly milk composition and DMI in 2 sequential observational trials. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Given the instability and high volatility of wind power generation, this study proposes a short-term wind power prediction method based on BWO‒VMD and TCN‒BiGRU to improve the accuracy of wind power prediction and better support the energy transition under the “dual carbon” strategy.MethodsA short-term wind power generation prediction model based on the beluga whale optimization (BWO) algorithm, variational mode de-composition (VMD), temporal convolutional network (TCN), and bidirectional gated recurrent unit (BiGRU) was carefully proposed to improve the prediction accuracy of wind power generation, particularly considering its inherent instability and high volatility. …”
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Shuffle Model of Differential Privacy: Numerical Composition for Federated Learning by Shaowei Wang, Sufen Zeng, Jin Li, Shaozheng Huang, Yuyang Chen

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Comprehensive objective function- guided decomposition-prediction co-optimization framework: Enhanced Transformer model for high-accuracy forecasting of non-stationary runoff by Xiaoqi Guo, Xuehua Zhao, Xueping Zhu, Bowen Zhu, Qiucen Guo, Xixi Wu, Huifang Wang, Jiatong An

“…Study region: In the Fen River Basin: Study focus: This study proposes a novel monthly runoff forecasting framework that integrates a Comprehensive Objective Function (COF) to guide the optimization of a hybrid model combining Sequential Variational Mode Decomposition (SVMD) and an enhanced Transformer (BGST). …”
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Multi-Scale Graph Attention Network Based on Encoding Decomposition for Electricity Consumption Prediction by Sheng Huang, Huakun Que, Lukun Zeng, Jingxu Yang, Kaihong Zheng

“…By emphasizing the impact of these experiential electricity consumption fluctuations on the current prediction process, we can capture the volatility variations to alleviate the over-smoothing problem. …”
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Analytical Study of Stud Shear Connector Behavior in Steel–UHPC Composite Structures by Wei Du, Zhijian Hu, Zhi Zhou

“…The proposed analytical model effectively captures variations in stud diameter and concrete elastic modulus, providing a load–slip curve with broader applicability than traditional empirical formulas. …”
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Experiment and simulation of single diamond abrasive particle scratching RB-SiC composite material by Dehan ZHANG, Kang DING, Xintong CAI, Feng YANG, Zhigang DONG, Yan BAO, Xiaoguang GUO, Renke KANG

“…To investigate the material removal mechanism and the surface damage causes during the grinding process of RB-SiC composite materials, the ABAQUS finite element software is used for scratch simulation and the scratching experiment of a single diamond abrasive indenter is used for verification.MethodsBased on ABAQUS finite element simulation software, a scratch simulation model of RB-SiC composite material with a multiphase structure is constructed. …”
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Optimal Selection Criterion for Runoff Component Models Based on Benefit-Risk Balance by DING Xiao-ling, HU Wei-zhong, TANG Hai-hua, LUO Bin, FENG Kuai-le

“…However, a unified criterion for selecting model forms that adapt to variations in runoff series length over time is still lacking, making it difficult to determine the types of runoff components and the order of their separation during modeling. …”
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Frequency–Spatial–Temporal Domain Fusion Network for Remote Sensing Image Change Captioning by Shiwei Zou, Yingmei Wei, Yuxiang Xie, Xidao Luan

“…The Spatia–Temporal Modeling module is further developed to employ state-space guided sequential scanning to capture evolutionary patterns of geospatial changes across temporal dimensions. …”
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Optimization of In_xGa_1−xN P-I-N Solar Cells: Achieving 21% Efficiency Through SCAPS-1D Modeling by Hassan Abboudi, Walid Belaid, Redouane En-nadir, Ilyass Ez-zejjari, Mohammed Zouini, Ahmed Sali, Haddou El Ghazi

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Development of craquelure patterns in paintings on canvas by Marcin Bury, Łukasz Bratasz

“…A simple procedure of calculating stress variations along the diagonal—using the function—on a sequential addition of cracks was developed. …”
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Integrated OVMD-BiGRU-SMAC Framework for Forecasting Construction Accidents in the Kingdom of Saudi Arabia by Badr T. Alsulami, Afaq Khattak

“…To enhance the predictive accuracy, the hyperparameters of each BiGRU model are optimized using the Sequential Model-based Algorithm Configuration (SMAC) technique. …”
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Surface discrepant manifestation, regime and controlling mechanisms of hydro-thermal behaviors in a typical high-temperature geothermal system on Tibetan Plateau by Yong Xiao, Yuqing Zhang, Jie Wang, Gongxi Liu, Peng Zhou, Huizhu Chen, Wenxu Hu, Liwei Wang, Limao Qin, Lianhe Zhou, Pengtian Ma, Qiong Pu

“…New hydrological insights for the region: Hydro-thermal manifestations within the valley exhibit significant spatial variations in water temperature, hydrochemical and isotopic compositions, as well as the travertine deposition. …”
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