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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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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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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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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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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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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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…In addition, experiments are conducted not only on the main dataset but also extended to January and August data, which represent seasonal differences, for generalization to verify the re-liability and broad applicability of the model. The verification results indicate that the constructed model effectively handles various datasets and complex time series features, with strong robustness and generality, and can run stably and efficiently in various practical scenarios.ConclusionsThe decomposition of raw wind power data is primarily examined using the OVMD algorithm in this study. …”
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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

“…To this end, we propose an encoding decomposition-based multi-scale graph neural network (CMNN). …”
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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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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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