Detecting memberships in multiplex networks via nonnegative matrix factorization and tensor decomposition by Fengqin Tang, Xiaozong Wang, Xuejing Zhao, Chunning Wang

“…Our method first clusters the layers using matrix factorization with graph regularization, followed by a tensor decomposition strategy enhanced by a corner-finding algorithm to uncover the nodes’ mixed memberships in each group. …”
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Metal commodity futures price forecasting based on a hybrid secondary decomposition error-corrected model by Yuetong Zhang, Ying Peng, Yuping Song

“…Finally, two predicted sequences are reconstructed to obtain the final one-step result, and based on the result of the one-step prediction, the two-step prediction is made using the sliding prediction method. The empirical results show that compared to the one-time decomposition model, the prediction accuracy of the secondary decomposition error correction model is improved by about 32%, 33%, and 22% respectively under single machine learning, ensemble machine learning, and deep learning models. …”
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Integrated Method of Future Capacity and RUL Prediction for Lithium‐Ion Batteries Based on CEEMD‐Transformer‐LSTM Model by Wangyang Hu, Chaolong Zhang, Laijin Luo, Shanhe Jiang

“…Considering nonlinear changes in the aging trajectory of lithium‐ion batteries, a method for predicting the RUL of lithium‐ion batteries was proposed in this study based on a complementary ensemble empirical mode decomposition (CEEMD) as well as transformer and long short‐term memory (LSTM) neural network dual‐drive machine learning model. …”
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Identification of Dielectric Response Parameters of Pumped Storage Generator-Motor Stator Winding Insulation Based on Sparsity-Enhanced Dynamic Decomposition of Depolarization Curr... by Guangya Zhu, Shiyu Ma, Shuai Yang, Yue Zhang, Bingyan Wang, Kai Zhou

Subjects: “…polarization/depolarization current method…”
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Chemical kinetic models, reaction mechanism estimation, and thermodynamic parameters for the non-isothermal decomposition of trona ore by Ceren Eda Delikurt, Meltem Kizilca Coruh

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Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction by L. Raymond Guo, Jifu Tan, M. Courtney Hughes

“…This study explores applying DMD in public health using lung cancer data and compares it with other machine learning models.MethodsWe analyzed lung cancer incidence data (2000–2021) from 1,013 US counties. …”
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A Hybrid Deep Learning Model Based on FFT-STL Decomposition for Ocean Wave Height Prediction by Yelian Sun, Longkun Yu, Dandan Zhu

“…To improve the accuracy of ocean wave height prediction, we developed a hybrid model that integrates decomposition and deep learning. …”
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A reduced simulation applied to viscoelastic fatigue of polymers using a time multi-scale approach based on partition of Unity method by Sebastian Rodriguez, Angelo Pasquale, Jad Mounayer, Diego Canales, Marianne Beringhier, Chady Ghnatios, Amine Ammar, Francisco Chinesta

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A Novel Framework for Solar Irradiance Prediction Integrating Signal Decomposition With Hybrid Time-Series Models by Keng-Hsi Lin, Po-Yen Hsu, Po-Han Chen, Mu-Yen Chen

“…Three decomposition methods—EMD, EEMD, and CEEMDAN—were combined with models such as LSTM, Bi-LSTM, GRU, Transformer, and statistical models such as ARIMA, ARCH, and GARCH were also implemented. …”
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A task decomposition and scheduling model for power IoT data acquisition with overlapping data efficiency optimization by Jindong Cui, Yuqing Wang, Zengchen Zhu, Ruotong Li

“…This paper proposes a data acquisition task decomposition and scheduling method optimized through overlapping data analysis. …”
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Model and Algorithm of Cooperative Optimization Decomposition for Short-Term Contract Electricity Considering Wind Power Uncertainty by Lingjie LIU, Jikeng LIN

“…A new cooperative optimization decomposition model and algorithm of short-term contract electricity is therefore proposed with consideration of the wind power uncertainty and maintenance plans. …”
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Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

“…Conventional prediction methods, such as physical and statistical models, often struggle to capture the complex nonlinear and nonstationary characteristics of streamflow. …”
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Model Decomposition-Based Approach to Optimizing the Efficiency of Wireless Power Transfer Inside a Metal Enclosure by Romans Kusnins, Sergejs Tjukovs, Janis Eidaks, Kristaps Gailis, Dmitrijs Pikulins

“…In the present study, the model decomposition method is adapted to substantially accelerate the process of finding the optimal WPT system parameters. …”
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Application of DTCWT Decomposition and Partial Differential Equation Denoising Methods in Remote Sensing Image Big Data Denoising and Reconstruction by Wei Zeng

“…To solve this problem, this research proposes an improved remote sensing image processing model, in which the dual tree complex wavelet transform (DTCWT) method is used to conduct multiscale decomposition of the impact, and the fourth-order differential equation is used to denoise the decomposed complex high-frequency subband information, and then the denoised subbands are reconstructed into the denoised image. …”
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A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models. by Mouad Klai, Olivier Monga, Mohamed Soufiane Jouini, Valérie Pot

“…To validate our VGA, we compare it with LBioS, a 3D model that integrates diffusion (via the Lattice Boltzmann method) with biodegradation, and Mosaic, a Pore Network Geometrical Modelling (PNGM) which represents the pore space using geometrical primitives. …”
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A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation by Mumtaz Ali, Ramendra Prasad, Salman Alamery, Aitazaz Ahsan Farooque

“…In this paper, a weekly solar radiation (SR) forecasting model is designed using a robust local mean decomposition (RLMD) technique unified with a random forest (RF) algorithm to generate a fully optimised hybridized RLD-RF model that has a promising capability to forecast the SR values. …”
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Incremental Gate State Output Decomposition Model for Highway Traffic Forecasting Using Toll Collection Data by Liang Yu, Ming Li, Kaifeng Liu, Xiangping Cheng

“…The proposed method improves the ability of the RNN model to estimate traffic data series by segmenting consecutive time intervals and accumulating incremental changes across these time intervals, allowing for more precise traffic predictions. …”
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Modeling and nonlinear analysis of chaotic wave processes in electrochemically active neuronal media based on matrix decomposition by A. M. Krot, S. I. Pavlov

“…A general model of the origin and evolution of chaotic wave processes in electrochemically active neuronal media based on the proposed method of matrix decomposition of operators of nonlinear systems has been developed. …”
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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

“…In order to eliminate the end effects, this paper proposes an extended model based on the principle of peak cross-correlation for improved empirical modal decomposition (EMD). …”
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Benzoyl peroxide decomposition on the surface of carbon materials on the base of activated carbon KAU by D. M. Haliarnyk, E. M. Demianenko, O. M. Bakalinska, T. V. Kulyk, B. B. Palyanytsya, A. G. Grebenyuk, V. S. Kuts, M. T. Kartel

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