MODELING OF THE LITHOSPHERE IN THE WHITE SEA REGION USING DECOMPOSITION OF ANOMALOUS GRAVITATIONAL AND MAGNETIC FIELDS by B. Z. Belashev, L. I. Bakunovich, N. V. Sharov

“…The decompositions of the fields were provided by the singular spectral method in the software package "R 4.3.1". …”
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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

“…However, the nonlinear and non-stationary characteristics of ET_o time series pose challenges for conventional prediction models. 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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Effects of Medicare predictors in health disparities in the risk of Alzheimer's disease by Igor Akushevich, Arseniy Yashkin, Julia Kravchenko

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An Approximate Analytical View of Fractional Physical Models in the Frame of the Caputo Operator by Mashael M. AlBaidani, Abdul Hamid Ganie, Adnan Khan, Fahad Aljuaydi

“…We examined the assumed model in fractional form in order to demonstrate and verify the efficacy of the new methods. …”
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Stochastic Optimization Scheduling Method for Mine Electricity–Heat Energy Systems Considering Power-to-Gas and Conditional Value-at-Risk by Chao Han, Yun Zhu, Xing Zhou, Xuejie Wang

“…To fully accommodate renewable and derivative energy sources in mine energy systems under supply and demand uncertainties, this paper proposes an optimized electricity–heat scheduling method for mining areas that incorporates Power-to-Gas (P2G) technology and Conditional Value-at-Risk (CVaR). …”
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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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The Impact of Dividend Policy on Liquidity Risk Components Based on Covariance Decomposition by Hamidreza Moazeni, Saeed Fathi

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3D Multi-Domain MFS Analysis of Sound Pressure Level Reduction Between Connected Enclosures by Luıs GODINHO, Fernando G. BRANCO, Paulo AMADO MENDES

“…It is important to note that, for such a configuration, a tra- ditional single-domain approach using methods like the MFS or the BEM would lead to undetermined equation systems, and thus the proposed model makes use of a domain decomposition technique.…”
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Logarithmic Mean Divisia Index Analysis and Dynamic Back Propagation Neural Network Prediction of Transport Carbon Emissions in Henan Province by Changjiang Mao, Jian Luo, Shengyang Jiao, Bin Zhao

“…This study applied the LMDI decomposition method and a BP neural network model to thoroughly analyse the factors influencing carbon emissions in Henan Province’s transportation sector and forecast future trends. …”
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Singular Vectors in Acoustic Simulation Tests of St. Paul the Apostle Church in Bochnia by Krzysztof KOSAŁA

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Calculating the true level of predictors significance when carrying out the procedure of regression equation specification by Nikita A. Moiseev

Subjects: “…regression models…”
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Accelerated Convergence Method for Flow Field Based on DMD-POD Combined Reduced-Order Optimization Model by Jianhui Li, Jun Huang, Yahui Sun, Guoqiang Li

“…This method involves conducting dynamic mode decomposition (DMD) and proper orthogonal decomposition (POD) model reduction on the field snapshots. …”
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A Rapid Computational Method for Quantifying Inter-Regional Air Pollutant Transport Dynamics by Luoqi Yang, Guangjie Wang, YeGui Wang, Yibai Wang, Yongjing Ma, Xi Zhang

“…The model integrates high-resolution numerical simulations, Geographic Information System (GIS) capabilities, and advanced statistical evaluation metrics with boundary pixel decomposition methods to effectively characterize complex pollutant transport dynamics while ensuring computational efficiency. …”
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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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Improved method of non-intrusive load monitoring based on compressed sensing by Bo Yuan, Hong Liu, Shaoyun Ge, Guoping Liu

“…Experiment shows that the NILM-CS and its improved methods proposed in this paper are reasonable. The load decomposition accuracy of NILM-CS is greater than 92 %, and the load identification accuracy is close to 90 %, whose effect is similar to traditional compression method but reduces sampling frequency by 50 %, and is superior to traditional NILM with same-frequency sampling by 1 ∼ 5 percentage points. …”
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Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Yanzi Li, Cai Chen, Fuqiang Liu, Jian Wang

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First-principle modeling of parallel-flow regenerative kilns and their optimization with genetic algorithm and gradient-based method by Michael Kreitmeir, Bruno Villela Pedras Lago, Ladislaus Schoenfeld, Sebastian Rehfeldt, Harald Klein

“…We present a one-dimensional first-principle model for parallel-flow regenerative kilns that accounts for the most important effects. …”
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Method for compensating multi-time measurement data of distribution network based on alternating minimization matrix completion combined with VMD-ARIMA-LSTM by Xiaodan Yu, Ruijia Jiang, Xiaolong Jin, Hongjie Jia, Yunfei Mu, Wei Wei, Wanxin Tang

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Complex, Temporally Variant SVD via Real ZN Method and 11-Point ZeaD Formula from Theoretics to Experiments by Jianrong Chen, Xiangui Kang, Yunong Zhang

“…Then, by using the real zeroing neurodynamics (ZN) method, matrix vectorization, Kronecker product, vectorized transpose matrix, and dimensionality reduction technique, a dynamical model, termed the continuous-time SVD (CTSVD) model, is derived and investigated. …”
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TR-SNN: a lightweight spiking neural network based on tensor ring decomposition by Shifeng Mao, Baoxin Yang, Hongze Sun, Wuque Cai, Daqing Guo

“…Nevertheless, these methods often involve complex training processes and are prone to significant accuracy loss.Methods In this work, we propose a novel TR-SNN model that achieves parameter compression using tensor ring decomposition. …”
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