Numerical simulation study on the evolution of wrinkling defects in carbon fiber laminates based on spatial decomposition damage variable method by ZHENG Haocheng, ZHOU Bo, LI Hui, WANG Yajie, SUN Ning, ZHANG Xueyan

“…In order to investigate the compression damage evolution of carbon fiber laminates with wrinkles and accurately predict the mechanical behavior of damage initiation and propagation, a progressive damage finite element model was proposed based on three-dimensional elastic theory by employing a spatial decomposition of damage variables method to establish the damage constitutive relation. …”
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SYNTACTIC HOMONYMS IN THE MODERN RUSSIAN LANGUAGE (VARIABILITY AND RE-DECOMPOSITION) by Igor I. Menshikov

“…The aim of the article is to analyse syntactic homonyms in the modern Russian language, mainly variability and re-decomposition. Generally homonyms are understood as a sound coincidence of various linguistic units, the meanings of which are not related to each other. …”
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RESEARCH OF EXISTENCE OF RELATIONSHIP BETWEEN VARIABLES BY THE METHOD OF CONDITION-CONSEQUENCE DECOMPOSITION OF EVENTS by V. Dron'

“…In the work an algorithm for establishing the existence of relationship between arbitrary socio-economic variables is given. The algorithm is based on the condition-consequence decomposition of events. …”
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Modeling and numerical simulation of Maxwell nanofluid flow with heat generation and convective heating: a combined Adomian decomposition method and Mohand transform by M. M. Khader, M. Adel, Mohammed Messaoudi

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Chaos in Fractional-Order Glucose–Insulin Models with Variable Derivatives: Insights from the Laplace–Adomian Decomposition Method and Generalized Euler Techniques by Sayed Saber, Emad Solouma, Rasmiyah A. Alharb, Ahmad Alalyani

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Improved Pacific Decadal Oscillation Prediction by an Optimizing Model Combined Bidirectional Long Short-Term Memory and Multiple Modal Decomposition by Hang Yu, Junbo Lei, Pengfei Lin, Tao Zhang, Hailong Liu, Huilin Lai, Lindong Lai, Bowen Zhao, Bo Wu

“…This study develops a BiLSTM-WOA-MMD (BWM) model, which integrates a bidirectional long short-term memory network with a whale optimization algorithm (WOA) and multiple modal decomposition (MMD), to forecast PDO at both interannual and decadal time scales. …”
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A Method for Solving LiDAR Waveform Decomposition Parameters Based on a Variable Projection Algorithm by Ke Wang, Guolin Liu, Qiuxiang Tao, Luyao Wang, Yang Chen

“…It can also provide a new method for parameter estimation in the Gaussian model for LiDAR waveform decomposition.…”
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A Forecast Model for COVID-19 Spread Trends Using Blog and GPS Data from Smartphones by Ryosuke Susuta, Kenta Yamada, Hideki Takayasu, Misako Takayasu

“…By employing time series’ trend decomposition and Spearman’s rank correlation, we identify and select a set of significant variables from the GPS and blog data to construct two models: a fixed-period model and a sequential adaptive model that updates with each new wave of infections. …”
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Prediction of the monthly river water level by using ensemble decomposition modeling by Chaitanya Baliram Pande, Lariyah Mohd Sidek, Bijay Halder, Okan Mert Katipoğlu, Jitendra Rajput, Fahad Alshehri, Rabin Chakrabortty, Subodh Chandra Pal, Norlida Mohd Dom, Miklas Scholz

“…Similarly, in the testing phase, the best two models performances are very well as a CEEMDAN-RF (R2:0.94) and CEEMDAN-RS (R2:0.90) in second combination variables, and the first combination variables based SVM- Linear (R2:0.93) and RF (R2:0.89) models are performance higher compared with other models. …”
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Capacity allocation method for a hybrid energy storage system participating in secondary frequency regulation based on variational mode decomposition by Taiying Zheng, Minghao Ye, Qinghua Wu

“…This paper introduces a method for configuring the capacity of a HESS engaged in the secondary frequency regulation, utilizing Variable Mode Decomposition (VMD). An economic model for a HESS, considering lifecycle costs and frequency regulation benefits, is constructed to maximize net income. …”
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Eigen‐Swarm: Swarm's Thermospheric Mass Density Modeling via Eigen‐Decomposition by Charles Owolabi, Hyunju Connor, Don Hampton, Denny M. Oliveira, Andres Calabia, V. Sai Gowtam, Eftyhia Zesta

“…We employ the Eigen‐Decomposition technique to extract dominant spatio‐temporal modes, with the first three capturing 99.12% of the variance, forming the basis of the Swarm‐based Eigen‐Decomposition model. …”
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Advances and applications of empirical mode decomposition and its variants in hydrology: A review by CHEN Yunfei, LIU Zuyu, LIU Xiuhua, HE Junqi, ZHENG Ce, MA Yandong

“…We provide a comprehensive overview of the fundamental theory, methodological characteristics, and current challenges of EMD, covering five EMD-based methods: Hilbert-Huang Transform (HHT), Ensemble Empirical Mode Decomposition (EEMD), Multivariate Empirical Mode Decomposition (MEMD), Extreme Point Symmetric Mode Decomposition (ESMD), and Variational Mode Decomposition (VMD). …”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

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Evaluation of Eight Decomposition-Hybrid Models for Short-Term Daily Reference Evapotranspiration Prediction by Yunfei Chen, Zuyu Liu, Ting Long, Xiuhua Liu, Yaowei Gao, Sibo Wang

“…Given this, in this study we evaluate eight decomposition-hybrid models that integrate various decomposition techniques with a long short-term memory (LSTM) network to enhance short-term (5-day, 7-day, and 10-day) ET_o forecasting. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Numerical benchmarking of dual decomposition-based optimization algorithms for distributed model predictive control by Vassilios Yfantis, Achim Wagner, Martin Ruskowski

“…This paper presents a benchmark study of dual decomposition-based distributed optimization algorithms applied to constraint-coupled model predictive control problems. …”
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A Hybrid Model for Carbon Price Forecasting Based on Secondary Decomposition and Weight Optimization by Yongfa Chen, Yingjie Zhu, Jie Wang, Meng Li

“…Secondly, a two-stage feature-selection method is employed, in which the partial autocorrelation function (PACF) is used to select relevant lagged features, while the maximal information coefficient (MIC) is applied to identify key variables from both historical and external data. Finally, this paper introduces a dynamic integration module based on sliding windows and sequential least squares programming (SLSQP), which can not only adaptively adjust the weights of four base learners but can also effectively leverage the complementary advantages of each model and track the dynamic trends of carbon prices. …”
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Data‐Driven Feature Decomposition Integrated Prediction Model for Dust Concentration in Open‐Pit Mines by Shuangshuang Xiao, Jin Liu, Qing Yang, Zhiguo Chang, Yonggui Zhang

“…The original data on dust concentration is not only nonstationary, nonlinear, and nonperiodic but also exhibits high complexity and variability. The decomposition ensemble prediction model can accurately forecast the dust concentration in open‐pit mines. …”
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A spectral analysis of chaotic oscillations in simulation model of Chua’s circuit developed with use of matrix decomposition by A. M. Krot, U. A. Sychou

“…The obtained terms are the basis of the simulation model used for carrying out computational experiments. …”
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A Decomposition-Based Stochastic Multilevel Binary Optimization Model for Agricultural Land Allocation Under Uncertainty by Fan Wang, Youxi Luo, Wenkai Zhang, Yanshu Yu

“…This study developed a decomposition-based stochastic multilevel binary optimization model for agricultural plot management. …”
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