A P2P Electricity-Carbon Trading Mechanism for Distributed Prosumers Based on Carbon Emission Flow Model by ZHAN Bochun, FENG Changsen, WANG Xiaohui, ZHANG Heng, MA Junwei, WEN Fushuan

“…Based on the improved Benders decomposition method, the original problem is decomposed into the main problem considering network constraints and the subproblem of optimal scheduling for prosumers. …”
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Flow Field Prediction of Gas-Solid Fluidized Bed Based on POD and Surrogate Model by Jialei FENG, Xiaohui ZHAO, Nan TU, Jiabin FANG, Ruihe HU, Yibo XU

“…The gas-solid two-phase flow process in the fluidized bed was predicted by adopting the POD-RBF method and the POD-Kriging method, respectively. Besides, the reduced-order model solutions with different gas velocities were compared with the full-order model solutions, and the effect of gas velocity on the bed motion was also studied. …”
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Reinforcing Moving Linear Model Approach: Theoretical Assessment of Parameter Estimation and Outlier Detection by Koki Kyo

“…Second, we enhance the extended ML (EML) model by introducing a new outlier detection and estimation method that identifies both the number and locations of outliers by maximizing the reduction in AIC. …”
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Computational and Numerical Analysis of the Caputo-Type Fractional Nonlinear Dynamical Systems via Novel Transform by Mashael M. AlBaidani, Fahad Aljuaydi, Shahad Abdullah F. Alsubaie, Abdul Hamid Ganie, Adnan Khan

“…Additionally, we compared our results with those of the homotopy decomposition method, the natural decomposition method, and the modified Mittag-Leffler function method. …”
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CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…To address this problem, this paper proposes a feature extraction method based on the combination of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Fuzzy Entropy (FN). …”
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Three-stage hybrid modeling for real-time streamflow prediction in data-scarce regions by Awad M. Ali, Mohammed Abdallah, Babak Mohammadi, Hussam Eldin Elzain

“…These findings underscore the importance of signal decomposition for refining data-driven models, facilitating better hydrological prediction and decision-making in data-scarce regions.…”
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Acoustic Emission Monitoring Method for Multi-Strand Fractures in Post-Tensioned Prestressed Hollow Core Slab Bridges Using Waveguide Rods by Wei Yan, Shiwei Niu, Wei Liu, Juan Li, Shu Si, Xilong Qi, Shengli Li, Nan Jiang, Shuhan Chen, Guangming Wu

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Gear Fault Diagnosis Based on Empirical Mode Decomposition and 1.5 Dimension Spectrum by Jianhua Cai, Xiaoqin Li

“…Aiming at the nonlinear and nonstationary feature of mechanical fault vibration signal, a new fault diagnosis method, which is based on a combination of empirical mode decomposition (EMD) and 1.5 dimension spectrum, is proposed. …”
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Forecasting long-time dynamics in quantum many-body systems by dynamic mode decomposition by Ryui Kaneko, Masatoshi Imada, Yoshiyuki Kabashima, Tomi Ohtsuki

“…Despite the simplicity of the method, the effectiveness and applicability of the DMD in quantum many-body systems such as the Ising model in the transverse field at the critical point are demonstrated, even when the time evolution at long time exhibits complicated features such as a volume-law entanglement entropy and consequential power-law decays of correlations characteristic of systems with long-ranged quantum entanglements unlike fluid dynamics. …”
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A Multi-Scale Unsupervised Feature Extraction Network with Structured Layer-Wise Decomposition by Yusuf Şevki Günaydın, Baha Şen

“…Experimental results on classification and image segmentation tasks show that the proposed method enhances model performance by enriching input representations. …”
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The Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Iterative Random Forest by Xiwen Qin, Jiajing Guo, Xiaogang Dong, Yu Guo

“…Aiming at the research of rotating mechanical bearing data, a fault identification method based on Variational Mode Decomposition (VMD) and Iterative Random Forest (iRF) classifier is proposed. …”
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Multi-Satellite Task Parallelism via Priority-Aware Decomposition and Dynamic Resource Mapping by Shangpeng Wang, Chenyuan Zhang, Zihan Su, Limin Liu, Jun Long

“…To address these problems, this paper proposes a task decomposition and resource mapping method based on task priorities and resource constraints. …”
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Decomposition Characteristics and Kinetics of Microalgae in N2 and CO2 Atmospheres by a Thermogravimetry by Xu Qing, Ma Xiaoqian, Yu Zhaosheng, Cai Zilin, Ling Changming

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Enhancing multi-temporal drought forecasting accuracy for Iran: Integrating an innovative hidden pattern identifier, recursive feature elimination, and explainable ensemble learnin... by Mahnoosh Moghaddasi, Mansour Moradi, Mehdi Mohammadi Ghaleni, Mehdi Jamei

“…Additionally, the effectiveness of the suggested model (HPFE-ETR) was assessed and contrasted with two common methods, Time-Varying Filter-based Empirical Mode Decomposition (TVF-EMD) and Variational Mode Decomposition (VMD), both of which were combined with ETR. …”
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Multityped Community Discovery in Time-Evolving Heterogeneous Information Networks Based on Tensor Decomposition by Jibing Wu, Lianfei Yu, Qun Zhang, Peiteng Shi, Lihua Liu, Su Deng, Hongbin Huang

“…A tensor decomposition framework, which integrates tensor CP factorization with a temporal evolution regularization term, is designed to model the multityped communities and address their evolution. …”
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A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport by Andreas Bärmann, Alexander Martin, Jonasz Staszek

“…The objective function of this model makes sure that as many trains as possible are running. …”
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Block-Based Multicut Benders Decomposition Algorithm for Transmission and Energy Storage Co-Planning by Edimar José de Oliveira, Arthur Neves de Paula, Leonardo Willer de Oliveira, Leonardo de Mello Honório

“…This division makes it possible to use parallel computation methods to solve each block simultaneously, reducing the simulation time, which allows the use of a more extensive time window to model the variability of random variables of the system, such as wind and load. …”
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An experimental analysis method for the incident sound field using propagation mode expansion: Study on the incident sound field in the insulation performance measurement for parti... by Yu Aida, Naohisa Inoue, Tetsuya Sakuma

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Short-term output prediction of wind-photovoltaic power based on time-frequency decomposition by Yangfan Zhang, Xuejiao Fu, Yaohan Wang, Zhengyu Wang, Xiaoxiao Wang

“…The proposed time-frequency decomposition with the smallest root mean square error of 0.92 and mean absolute error of 0.58 in photovoltaic prediction, at the same time, the smallest root mean square error of 67.5 and mean absolute error of 48.16 in wind power prediction, significantly outperforming other power prediction methods.…”
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Enhancing Image Denoising Performance of Bidimensional Empirical Mode Decomposition by Improving the Edge Effect by Feng-Ping An, Da-Chao Lin, Xian-Wei Zhou, Zhihui Sun

“…This approach includes two steps, in which the first one is an extrapolation operation through the regression model constructed by the support vector machine (SVM) method with high generalization ability, based on the information of the original signal, and the second is an expansion by the closed-end mirror expansion technique with respect to the extrema nearest to and beyond the edge of the data resulting from the first operation. …”
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