An Improved Short-Term Electricity Load Forecasting Method: The VMD–KPCA–xLSTM–Informer Model by Jiawen You, Huafeng Cai, Dadian Shi, Liwei Guo

“…This paper proposes a hybrid forecasting method (VMD–KPCA–xLSTM–Informer) based on variational-mode decomposition (VMD), kernel principal component analysis (KPCA), extended long short-term memory network (xLSTM), and the Informer model. …”
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Calculation models for acoustic analysis of sacral objects by Krzysztof KOSAŁA

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Short-Term Wind Power Prediction Method Based on CEEMDAN-VMD-GRU Hybrid Model by Na Fang, Zhengguang Liu, Shilei Fan

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An Alternative Framework for Dynamic Mode Decomposition with Control by Gyurhan Nedzhibov

“…The new scheme aims to improve computational efficiency while maintaining the reliability and accuracy of the decomposition. We provide a theoretical proof that the dynamic modes produced by the proposed method are exact eigenvectors of the corresponding Koopman operator. …”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…This paper presents an advanced decomposition-integration framework which seamlessly integrates econometric models with machine learning techniques to enhance carbon price forecasting. …”
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A photovoltaic power forecasting method based on the LSTM-XGBoost-EEDA-SO model by Ying Xu, Xinrong Ji, Zhengyang Zhu

“…Experimental results demonstrate that the proposed model significantly outperforms standalone benchmark methods. …”
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Modeling within-host Chikungunya virus dynamics with the immune system using semi-analytical approaches by Morufu Oyedunsi Olayiwola, Akeem Olarewaju Yunus, Adedapo Ismaila, Alaje, Joseph Adeleke Adedeji

“…The Laplace Adomian Decomposition Method (LADM) is used to solve the model. …”
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GPU Parallelization Nested Decomposition Method for Solving Large Linear Systems in Reservoir Numerical Simulation by Xin Shi, Yuan Di

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BS-CP: Efficient streaming Bayesian tensor decomposition method via assumed density filtering. by Jiaqi Liu, Qiwu Wu, Lingzhi Jiang, Renjun Zhan, Xiaochuan Zhao, Husheng Wu, Weicong Tan

“…CANDECOMP/PARAFAC (CP) is a popular tensor decomposition model, which is both theoretically advantageous and numerically stable. …”
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A Micro-Topography Enhancement Method for DEMs: Advancing Geological Hazard Identification by Qiulin He, Xiujun Dong, Haoliang Li, Bo Deng, Jingsong Sima

“…Geological hazards in densely vegetated mountainous regions are challenging to detect due to terrain concealment and the limitations of traditional visualization methods. This study introduces the LiDAR image highlighting algorithm (LIHA), a novel approach for enhancing micro-topographical features in digital elevation models (DEMs) derived from airborne LiDAR data. …”
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A structural health monitoring data reconstruction method based on VMD and SSA-optimized GRU model by Xiaoliang Jia, Guoyan Zhang, Zhiqiang Wang, Huacong Li, Jing Hu, Songlin Zhu, Caiwei Liu

“…To address this challenge, this study develops a method combining Variational Mode Decomposition (VMD) and Sparrow Search Algorithm (SSA)-optimized Gate Recurrent Unit (GRU) for recovering structural response data. …”
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A Novel Renewable Energy Scenario Generation Method Based on Multi-Resolution Denoising Diffusion Probabilistic Models by Donglin Li, Xiaoxin Zhao, Weimao Xu, Chao Ge, Chunzheng Li

“…To address this gap, this paper proposes a novel renewable energy scenario generation method based on a multi-resolution diffusion model. …”
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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…The paper proposes a methane outburst volume-prediction and early-warning method. This method is based on a secondary decomposition and improved TSMixer model. …”
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Day-ahead photovoltaic power generation forecasting with the HWGC-WPD-LSTM hybrid model assisted by wavelet packet decomposition and improved similar day method by Ruxue Bai, Jinsong Li, Jinsong Liu, Yuetao Shi, Suoying He, Wei Wei

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A Feature Extraction Method of Ship Underwater Noise Using Enhanced Peak Cross-Correlation Empirical Mode Decomposition Method and Multi-Scale Permutation Entropy by Peng Liu, Chen Dai, Shuaiqiang Li, Hui Jin, Xinfu Liu, Guijie Liu

“…A feature extraction method based on the combination of improved empirical modal decomposition (IEMD) and multi-scale permutation entropy (MPE) is proposed to address the problem of inaccurate recognition and classification of ship noise signals under complex environmental conditions. …”
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Analysis of a mathematical model for malaria using data-driven approach by Adithya Rajnarayanan, Manoj Kumar, Abdessamad Tridane

Subjects: “…Malaria model…”
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Combining Laplace transform and Adomian decomposition method for solving singular IVPs of Emden-Fowler of partial differential equations by Waleed Al-Hayani, Fatima Yassin

“…In this paper, the time-dependent Emden-Fowler type partial differential equations and wave-type equations with singular behavior at  are analytically solved using the combined Laplace transform and Adomain decomposition method (LT-ADM). To avoid the singularity behavior for both models at , the benefit of this single global technique is used to present a solid framework. …”
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ED-Stacking：A Construction Method of Few-shot Prediction Model for Beef Microbial Growth Based on Ensemble Learning by Hanqiang LI, Yi CHEN, Yufei GAO, Kun HOU, Liping SONG, Jing LI

“…First, empirical mode decomposition (EMD), discrete Fourier transform (DFT) and additive modeling were applied to construct a time series decomposition method EMD-DFT, which was used to extract the trend, period, and residual features in the microbial growth time series, and to provide training data for the subsequent prediction model. …”
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Deep attention model for arrhythmia signal classification based on multi-objective crayfish optimization algorithmic variational mode decomposition by Yihang Zhang, Hang Zhao

“…The ablation study was implemented to verify the effectiveness of the proposed signal decomposition method and deep attention modules. The performance of the model based on MOCOA-VMD achieves the best accuracy of 94.35%, much higher than the model constructed by modules of EEMD, VMD and CNN. …”
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A New Modified Technique of Adomian Decomposition Method for Fractional Diffusion Equations with Initial-Boundary Conditions by Saadia Masood, null Hajira, Hassan Khan, Rasool Shah, Saima Mustafa, Qasim Khan, Muhammad Arif, Fairouz Tchier, Gurpreet Singh

“…In this regard, a very prominent and accurate technique, which is known as the new technique of the Adomian decomposition method, is developed and presented for the solution of the initial-boundary value problem of the diffusion equation with fractional view analysis. …”
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