Fault tidentification method of outage transmission line based on convolutional neural network and wavelet packet decomposition by WANG Xinming, WANG Xiangyu, JIA Xiaobo, ZHANG Feifei, LI Shaobo, HU Yongqiang

“…For double-circuit transmission lines on the same tower, an outage line fault identification method using spectrum graph generated by wavelet packet decomposition as a convolutional neural network (CNN) input is proposed. …”
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Statistical package for computing precision covariance matrices via modified Cholesky decomposition by Elías D. Niño-Ruiz, Dylan Samuel Cantillo Arrieta, Giuliano Raffaele Frieri Quiroz, Nicolas Quintero Quintero

“…We introduce a statistical package designed to compute precision covariance matrices using modified Cholesky decomposition, tailored for Atmospheric General Circulation Models (AGCMs). …”
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A Spatial–Temporal Time Series Decomposition for Improving Independent Channel Forecasting by Yue Yu, Pavel Loskot, Wenbin Zhang, Qi Zhang, Yu Gao

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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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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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Study on nonlinear asymmetric thermomechanical stability of microsize FGM curved beams based on nonlocal couple stress curvature sensitive model by Saeid Sahmani, Kamila Kotrasova, Muhammad Atif Shahzad, Veronika Valaskova, Mona Zareichian, Babak Safaei

“…To originate the numerical curvature sensitive model, the radial point interpolation meshfree technique is utilized embracing the variation of the nodal points density based upon the background decomposition method (BDM). …”
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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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Existence, Uniqueness and Convergence Solution of Nonlinear Caputo-Fabrizio Fractional Biological Population Model by Ali Khalouta

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A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization by Lizhi Cui, Zhihao Ling, Josiah Poon, Simon K. Poon, Junbin Gao, Paul Kwan

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Improved sub-band JND model with textural decomposition and its application in perceptual image coding by Ming-kui ZHENG, Kai-xiong SU, Wei-xing WANG, Cheng-dong LAN, Xiu-zhi YANG

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An Enhanced TimesNet-SARIMA Model for Predicting Outbound Subway Passenger Flow with Decomposition Techniques by Tianzhuo Zuo, Shaohu Tang, Liang Zhang, Hailin Kang, Hongkang Song, Pengyu Li

“…This research introduces a hybrid forecasting approach that combines an enhanced TimesNet model, Seasonal Autoregressive Integrated Moving Average (SARIMA), and Variational Mode Decomposition (VMD) to improve passenger flow prediction. …”
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Linear Model and Gradient Feature Elimination Algorithm Based on Seasonal Decomposition for Time Series Forecasting by Sheng-Tzong Cheng, Ya-Jin Lyu, Yi-Hong Lin

“…This study proposes a linear time series model architecture based on seasonal decomposition. …”
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Application of an improved LSTM model based on FECA and CEEMDAN VMD decomposition in water quality prediction by Jie Long, Chong Lu, Yiming Lei, Zhong Yuan Chen, Yihan Wang

“…Abstract To address the limitations of existing water quality prediction models in handling non-stationary data and capturing multi-scale features, this study proposes a hybrid model integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Variational Mode Decomposition (VMD), Long Short-Term Memory Network (LSTM), and Frequency-Enhanced Channel Attention (FECA). …”
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Rapid Prediction of Ice Accretion on Swept Wings Based on Proper Orthogonal Decomposition and Surrogate Modelling by J. Du, Q. Guo, Y. Yue, Y. Ma, H. Cheng

“…To enable rapid and accurate ice formation predictions on swept wings, this study proposes a prediction methodology integrating proper orthogonal decomposition (POD) and Kriging surrogate modelling. …”
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A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…Traditional forecasting methods demonstrate evident limitations in capturing the nonlinear characteristics and complex volatility patterns of price series, underscoring the necessity of developing high-precision prediction models. …”
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Photovoltaic Power Generation Forecasting Based on Secondary Data Decomposition and Hybrid Deep Learning Model by Liwei Zhang, Lisang Liu, Wenwei Chen, Zhihui Lin, Dongwei He, Jian Chen

“…Empirical tests on a PV dataset from an Australian solar power plant show that the proposed CECSVB-LSTM model significantly outperforms traditional single models and combination models with different decomposition methods, improving R² by more than 7.98% and reducing the root mean square error (RMSE) and mean absolute error (MAE) by at least 60% and 55%, respectively.…”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Comparative analysis with seven standalone and seven decomposition-based models confirmed the superior performance and statistical significance of the D3Net model. …”
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SIP-IFVM: A Time-evolving Coronal Model with an Extended Magnetic Field Decomposition Strategy by Haopeng Wang, Liping Yang, Stefaan Poedts, Andrea Lani, Yuhao Zhou, Yuhang Gao, Luis Linan, Jiakun Lv, Tinatin Baratashvili, Jinhan Guo, Rong Lin, Zhan Su, Caixia Li, Man Zhang, Wenwen Wei, Yun Yang, Yucong Li, Xinyi Ma, Edin Husidic, Hyun-Jin Jeong, Mahdi Najafi-Ziyazi, Juan Wang, Brigitte Schmieder

“…To address this, we propose an extended magnetic field decomposition strategy and successfully implement it in an implicit MHD coronal model. …”
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Statistical Analysis of Physical Characteristics Calculated by NEMO Model After Data Assimilation by Konstantin Belyaev, Andrey Kuleshov, Ilya Smirnov

“…The main goal of this study is to develop a method for finding the joint probability distribution of the state of the characteristics of the NEMO (Nucleus for European Modeling of the Ocean) ocean dynamics model with data assimilation using the Generalized Kalman filter (GKF) method developed earlier by the authors. …”
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Modeling a fractional-order chlamydia dynamic with protected intimacy as a strategic control intervention by Akeem Olarewaju Yunus, Morufu Oyedunsi Olayiwola, Mutahir Oluwafemi Abanikanda

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