Experience in modeling inclined cracks in materials with cubic crystal structure by Karina A. Mushankova, Larisa V. Stepanova

“…The atomic stress distributions associated with the crack tip are obtained using the molecular dynamics method. Continuum distributions are obtained from the theoretical solution of the problem of determining the stress-strain state at the crack tip, based on the methods of the elasticity theory of anisotropic media and the subsequent decomposition of complex potentials by eigenfunctions. …”
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Numerical method and application of transient electromagnetic full-time responses of pseudo-random waveforms by Kailiang LU, Jianhua YUE, Ya’nan FAN, Danyang XI

“…Firstly, the full-time domain electromagnetic forward modeling method for pseudo-random waveforms is introduced. …”
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A Forecasting Method for COVID-19 Epidemic Trends Using VMD and TSMixer-BiKSA Network by Yuhong Li, Guihong Bi, Taonan Tong, Shirui Li

“…Experimental results based on COVID-19 case data from Italy and the United States demonstrate that the proposed model significantly outperforms existing mainstream methods across various error metrics, achieving higher prediction accuracy and robustness.…”
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Transform-Based Multiresolution Decomposition for Unsupervised Learning and Data Clustering of Cellular Network Behavior by Juan Cantizani-Estepa, Sergio Fortes, Javier Villegas, Javier Rasines, Raul Martin Cuerdo, Raquel Barco

“…This work proposes a novel method that combines Multi-Resolution Analysis (MRA) by wavelet transforms and unsupervised clustering with pre-initialized Gaussian Mixture Models (GMMs) for the totally unsupervised grouping of cellular network behaviors using different metrics. …”
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Comparative analysis of water network minimization in industrial processes: Regeneration vs. non-regeneration methods by Khalifa Azza Mohamed, Elsayed Nadia Ali, Awad Mostafa

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Asynchronous time integration while achieving zero interface energy by Radim Dvořák, Radek Kolman, Jan Falta, Michaela Neühauserová

“…The numerical model is partitioned into individual subdomains using the domain decomposition method by means of localized Lagrange multipliers. …”
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Analyzing the dihedral scattering component of P-band SAR signals for trunk permittivity estimation – a concept study by Anke Fluhrer, Hamed Alemohammad, Thomas Jagdhuber

“…A new retrieval method, based on a hybrid decomposition technique and the extended (x-) Fresnel model, is proposed for estimating trunk permittivity from polarimetric P-band SAR observations. …”
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Fuzzy Solutions of Fuzzy Fractional Parabolic Integro Differential Equations by Deepak Pachpatte, Nagwa Saeed

“…This work primarily investigates the numerical solution of fuzzy fractional parabolic integro-differential equations of the Volterra type with the time derivative defined in the Caputo sense using the fuzzy Adomian decomposition method. Fuzzy fractional partial integro-differential equations pose significant mathematical challenges due to the interplay between fuzziness and fractional-order dynamics, while at the same time, there is a growing need for accurate and efficient methods to model real-world phenomena involving uncertainty in physics, biology, and engineering. …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…The proposed framework includes a new hybrid machine learning (ML) model based on generalized ridge regression and kernel ridge regression with a regularized locally weighted (GRKR) method. …”
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Short-Term Power Load Prediction Based on Level Processing Method and Improved GWO Algorithm by Yuntong Li

“…Comparative experiments are conducted among the proposed model, the long short-term memory model, as well as the variational mode decomposition model. …”
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An improved GRU method for slope stress prediction by Lichun Bai, Ronghui Zhao, Sen Lin, Zishu Chai, Xuan Wang

“…In order to address the aforementioned issues, the present paper proposes an intelligent prediction model based on Variational Mode Decomposition (VMD) and Dung Beetle Optimization (DBO), combined with an improved Gated Recurrent Unit (GRU), which is hereby referred to as the VMD-DBO-GRU-A model. …”
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A multi-objective mathematical model for the multi-warehouse order picking system using Benders decomposition algorithm by Fatemeh Nikkhoo, Ali Hosseinzadeh Kashan, Bakhtiar Ostadi, Ehsan Nikbakhsh

“…Also, the numerical results show the performance of the Benders decomposition algorithm and the accelerated Benders algorithm as suitable alternatives for solving the model in large-sized problems. …”
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Forecasting regional carbon prices in china with a hybrid model based on quadratic decomposition and comprehensive feature screening. by Yaoyang Yi

“…This work presents a hybrid model incorporating comprehensive feature screening, optimized quadratic decomposition, and the Optuna-Attention-LSTM prediction method, aiming to improve the accuracy and stability of carbon price prediction. …”
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Tuck-KGC: based on tensor decomposition for diabetes knowledge graph completion model integrating Chinese and Western medicine by Jiangtao ZhangSun, Yu Xin Yang, Beiji Zou, Qinghua Peng, Xiao Xia Xiao

“…To mitigate this, we propose the Tucker Decomposition Knowledge Graph Completion (Tuck-KGC) method, which incorporates entity types into the tensor decomposition framework. …”
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Application of Proper Orthogonal Decomposition in Spatiotemporal Characterization and Reduced-Order Modeling of Rotor–Stator Interaction Flow Field by Yongkang Lin, Weijian Yang, Hu Wang, Fazhong Wang, Jie Hu, Jianyao Yao

“…To address the high computational cost and resource demands arising from large-scale similar cases in multi-parameter excitation optimization and analysis, a reduced-order modeling (ROM) method based on time–space and parameter decoupling is proposed using multi-parameter POD. …”
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Enhanced Carbon Flux Forecasting via STL Decomposition and Hybrid ARIMA-ES-LSTM Model in Amazon Forest by Jean A. C. Dias, Pedro H. Do V. Guimaraes, Williane G. S. Pereira, Leonardo De O. Tamasauskas, Marivan S. Gomes, Alan B. S. Correa, Karla Figueiredo, Gilson Costa, Gabriel Brito Costa, Fernando A. R. Costa, Marcos C. Da R. Seruffo

“…The model integrates seasonal and trend decomposition using Loess (STL) with statistical methods (ARIMA and Exponential Smoothing-ES) and a machine learning technique (Long Short-Term Memory - LSTM). …”
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Low-Light Image Enhancement Integrating Retinex-Inspired Extended Decomposition with a Plug-and-Play Framework by Chenping Zhao, Wenlong Yue, Yingjun Wang, Jianping Wang, Shousheng Luo, Huazhu Chen, Yan Wang

“…To address these limitations, this paper presents an enhancement method by integrating a Plug-and-Play strategy into an extended decomposition model. …”
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A Posteriori Error Analysis for a Lagrange Multiplier Method for a Stokes/Biot Fluid-Poroelastic Structure Interaction Model by Houédanou Koffi Wilfrid

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Deep Learning-Based Vertical Decomposition of Ionospheric TEC into Layered Electron Density Profiles by Jialiang Zhang, Jianxiang Zhang, Zhou Chen, Jingsong Wang, Cunqun Fan, Yan Guo

“…This study proposes a deep learning-based vertical decomposition model for ionospheric Total Electron Content (TEC), which establishes a nonlinear mapping from macroscale TEC data to vertically layered electron density (Ne) spanning 60–800 km by integrating geomagnetic indices (AE, SYM-H) and solar activity parameters (F10.7). …”
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Predicting soil organic matter using corrected field spectra and stacking ensemble learning by Yu Wang, Xuhui Yan, Rongyanting Huo, Longcai Zhao, Jie Peng, Yongsheng Hong, Jing Liu

“…The study aims to assess the ability of spectra correction methods, including non-negative matrix decomposition (NMF), and generalized least squares weight (GLSW), when combined with the Stacking model, to predict SOM. …”
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