Identification of Microseismic Signals Based on Multiscale Singular Spectrum Entropy by Xingli Zhang, Zhenhua Zhao, Ruisheng Jia, Lianyue Cao

“…A microseismic signal identification method which combines variational mode decomposition (VMD) and multiscale singular spectrum entropy was proposed in this paper. …”
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Study of the physicochemical properties of the etravirine substance by S. A. Zolotov, E. S. Ponomarev, I. A. Dain, N. B. Demina, A. S. Zolotova

“…Study the etravirine physicochemical properties to model the design of studies to create an innovative dosage formMaterials and methods. …”
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Investigation of a transformer-based hybrid artificial neural networks for climate data prediction and analysis by Shangke Liu, Ke Liu, Zheng Wang, Yuanyuan Liu, Bin Bai, Rui Zhao

“…Compared to four different climate prediction decomposition methods, the proposed hybrid model with the Transformer method performs the best. …”
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A numerical algorithm based on Jacobi polynomials for FIDEs with error estimation by K. Sadri, D. Amilo, E. Hincal

“…Notably, our approach is simpler and more cost-effective compared to established methods such as Adomian decomposition, Homotopy perturbation, Sinc-collocation, and Legendre wavelet techniques. …”
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Asymptotically stable data-driven koopman operator approximation with inputs using total extended DMD by Louis Lortie, James Richard Forbes

“…The performance of the proposed method is then compared to the well-known extended dynamic mode decomposition (DMD) method and to the newly introduced forward–backward extended DMD method using a simulated Duffing oscillator dataset and experimental soft robot arm dataset.…”
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A hybrid machine learning and ied-based fault detection scheme for microgrids by Hamid Radmanesh, Abolfazl Hadadi

“…This paper proposes a new intelligent fault detection approach that leverages advanced signal processing techniques, including modified Variable Mode Decomposition (MVMD) for feature extraction, combined with a hybrid machine learning (ML) model. …”
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Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome. by Dragana M Pavlovic, Petra E Vértes, Edward T Bullmore, William R Schafer, Thomas E Nichols

“…Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. …”
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Uncertainty evaluation of surface profile measurement error based on adaptive sparse grid polynomial chaos expansion by Ke Zhang, Xinya Zheng, Ruiyu Zhang

“…This model is optimized using Cholesky decomposition to handle variable correlations, sparse grid integration for efficient generation of multidimensional integration points, and maximum entropy method for direct reconstruction of probability distributions, thereby achieving efficient evaluation of the measurement error and uncertainty of surface profile. …”
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A NEW ALGORITHM FOR ANALYSIS OF EXPERIMENTAL MÖSSBAUER SPECTRA by Natalia V. Baidakova, Nikolai I. Chernykh, Valerii M. Koloskov, Yurii N. Subbotin

“…Some model-free methods of the NGR spectra analysis have been implemented in a number of known algorithms. …”
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Emerging Translational Variance: Vacuum Polarization Energy of the ϕ6 Kink by H. Weigel

“…We propose an efficient method to compute the vacuum polarization energy of static field configurations that do not allow decomposition into symmetric and antisymmetric channels in one space dimension. …”
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Multiple Feature Vectors Based Fault Classification for WSN Integrated Bearing of Rolling Mill by Bo Qin, Luyang Zhang, Heng Yin, Yan Qin

“…To solve the above-mentioned problems, a fault extraction method is put forward to extract multiple feature vectors and then a classification model is developed. …”
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Multi-feature stock price prediction by LSTM networks based on VMD and TMFG by Zhixin Zhang, Qingyang Liu, Yanrong Hu, Hongjiu Liu

“…This paper proposes a novel stock price forecasting model—the Variational Mode Decomposition—Triangulated Maximally Filtered Graph—Long Short-Term Memory (VMD–TMFG–LSTM) combined model—aimed at improving prediction accuracy, stability, and computational efficiency. …”
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Studying the Photocatalytic Degradation of Tri-n-Butyl Phosphate Using Nano Nd-Doped TiO2 by H. Ghasemi Mobtaker, A. Malekinejad, T. Yousefi, H. Aghayan

“…Results showed that the method has high efficiency and is a promising procedure for decomposition of TBP.…”
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Fusion of PSO-SVM and ICEEMDAN for high stability GNSS-MR sea level height estimation by Linghuo Jian, Xinpeng Wang, Haining Hao, Hong Wang, Longshan Yang

“…The method utilises the GNSS multipath interfering signal frequencies (signal-to-noise oscillation term) extracted by ICEEMDAN as input features to the PSO-SVM model to retrieve the sea level height. …”
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OPTIMAL DESIGN OF SUSPENSION SYSTEM BASED ON IMPROVED PARTICLE SWARM-TABOO SEARCH ALGORITHM by WANG Jun, TIAN ZhongXu

“…In order to solve the natural frequency and mode shape of the suspension system,the method of combining the jorisk decomposition with the Jacobian method is used. …”
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Functional Data Analysis in Forecasting Serbian Fertility by Vladimir Nikitović

“…One of the most important benefits of the method reflected in confirmation that is essentially to model and forecast more than one principal component in order to adequately address sources of variation in fertility. …”
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Harnessing the Power of Improved Deep Learning for Precise Building Material Price Predictions by Zhilong Guo, Yayong Luo, Tongqiang Yi, Xiangnan Jing, Jing Ma

“…Additionally, a VMD decomposition mode number K value optimization method, based on a sparse index, is proposed. …”
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Large-Eddy Simulation of Unsteady Flow in a Mixed-Flow Pump by Chisachi Kato, Hiroshi Mukai, Akira Manabe

“…The method is implemented as a parallel program by applying a domain-decomposition programming model.…”
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The Leakage Identification and Location of Ship Pipeline System Based on Vibration Signal Processing by Pan Su, JieChang Wu, Guanghui Chang, Shuyong Liu, Xuejiao Feng

“…The test sample identification results show that the leak identification and localization method based on VMD-RBF has a high accuracy.…”
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Leveraging pleiotropy for joint analysis of genome-wide association studies with per trait interpretations. by Kodi Taraszka, Noah Zaitlen, Eleazar Eskin

“…We introduce pleiotropic association test (PAT) for joint analysis of multiple traits using genome-wide association study (GWAS) summary statistics. The method utilizes the decomposition of phenotypic covariation into genetic and environmental components to create a likelihood ratio test statistic for each genetic variant. …”
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