Groundwater Depth Forecasting Using a Coupled Model by Manfei Zhang, Yimeng Wang, Xiao Wang, Weibo Zhou

“…In this paper, a new method based on coupling wavelet decomposition method (WA), autoregressive moving average (ARMA) model, and BP neural network (BP) model for groundwater depth forecasting applications was proposed. …”
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Model-Based Deep Network for Single Image Deraining by Pengyue Li, Jiandong Tian, Yandong Tang, Guolin Wang, Chengdong Wu

“…In this paper, we use the screen blend model of Photoshop as the nonlinear rainy image decomposition model. …”
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Sines, transient, noise neural modeling of piano notes by Riccardo Simionato, Stefano Fasciani

“…This article introduces a novel method for emulating piano sounds. We propose to exploit the sine, transient, and noise decomposition to design a differentiable spectral modeling synthesizer replicating piano notes. …”
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Rolling Bearing Fault Diagnosis Based on Optimized VMD Combining Signal Features and Improved CNN by Yingyong Zou, Xingkui Zhang, Wenzhuo Zhao, Tao Liu

“…The experimental results show that the method can effectively extract fault features in noise-covered signals, and the accuracy is also significantly improved compared with traditional methods.…”
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Research on bearing fault diagnosis based on improved northern goshawk algorithm optimizing SVM by WU Xiaojun, LI Quwei

“…At the same time, the original diagnostic signals were feature extracted through wavelet packet decomposition and divided into 10 categories. The energy of each frequency band in the 3rd layer was used as the feature vector and input into the fault diagnosis model. …”
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A Data-Driven Observer for Wind Farm Power Gain Potential: A Sparse Koopman Operator Approach by Yue Chen, Bingchen Wang, Kaiyue Zeng, Lifu Ding, Yingming Lin, Ying Chen, Qiuyu Lu

“…This method lifts the low-dimensional wind direction input into a high-dimensional space of observable functions and then employs iterative sparse regression to identify a minimal, interpretable linear model in this lifted space. …”
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Modeling of Task Planning for Multirobot System Using Reputation Mechanism by Zhiguo Shi, Jun Tu, Yuankai Li, Junming Wei

“…Modeling of task planning for multirobot system is developed from two parts: task decomposition and task allocation. …”
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A Fusion Model for Predicting the Vibration Trends of Hydropower Units by Dong Liu, Youchun Pi, Zhengyang Tang, Hongpeng Hua, Xiaopeng Wang

“…To enable timely monitoring of unit performance, it is critical to investigate the trends in vibration signals, to enhance the accuracy and reliability of vibration trend prediction models. This paper proposes a fusion model for the vibration signal trend prediction of hydropower units based on the waveform extension method empirical mode decomposition (W-EMD) and long short-term memory neural network (LSTMNN). …”
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WORK OF A HIGHER EDUCATIONAL INSTITUTION MULTIDISCIPLINARY DEPARTMENT ON THE FORMATION OF PROFESSIONAL COMPETENCES OF FUTURE ELEMENTARY SCHOOL TEACHERS by E. G. Gutsu, E. I. Smirnova

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Empirical Reduced-Order Modeling for Boundary Feedback Flow Control by Seddik M. Djouadi, R. Chris Camphouse, James H. Myatt

“…Specifically, the proper orthogonal decomposition (POD) of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. …”
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Design of experiments for the stochastic unit commitment with economic dispatch models by Nahal Sakhavand, Jay Rosenberger, Victoria C.P. Chen, Harsha Gangammanavar

“…Typically, a sample average approximation of the true problem is solved using a cutting plane method (such as the L-shaped method) or scenario decomposition (such as Progressive Hedging) algorithms. …”
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MATHEMATICAL MODELS OF DECISION SUPPORT IN THE PROBLEMS OF LOGISTICS NETWORKS OPTIMIZATION by Володимир Валентинович Безкоровайний, Оксана Михайлівна Драз

“…To implement the method, mathematical models of problems of the procedure of ranking options in the technologies of project decision support have been developed, which allow to combine the advantages of the technologies of the ordinalistic and cardinalistic approaches. …”
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Fault analysis of chemical equipment based on an improved hybrid model. by Wu Huiyong, Kuan Jiang, Wang Yanyu

“…The method combines Variational Mode Decomposition (VMD), Least Mean Squares (LMS) processing, an asymmetric attention mechanism, and a pre-activation ResNet-BiGRU model to create an efficient framework for multimodal data fusion and analysis. …”
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Architecture modeling of satellite Internet simulation platform based on MBSE by LI Hongguang, LIU Yaoqi, ZHOU Yiqing, SHI Jinglin

“…The model-based systems engineering (MBSE) method was proposed to model the architecture of satellite Internet simulation platform. …”
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Integration and Modeling of Multi-Energy Network Based on Energy Hub by Min Mou, Yuhao Zhou, Wenguang Zheng, Yurong Xie

“…Based on the physical characteristics of energy systems such as power systems, thermal systems, and gas systems, this article studies the comprehensive power flow model including the electric-gas-thermal multi-energy coupling network and proposes the power flow decomposition of the energy supply subsystem and its applicable equation based on Newton–Raphson method. …”
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Heart Signal Analysis Using Multistage Classification Denoising Model by Ravi Raj Choudhary, Mamta Rani, Ranjit Kaur, Mahendra Bhadu

“…This method produced comparable results, with a 98.9% classification accuracy for signals, through the utilization of the CNN and LSTM model. …”
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Computational Analysis of Complex Population Dynamical Model with Arbitrary Order by Fazal Haq, Kamal Shah, Ghaus ur Rahman, Yongjin Li, Muhammad Shahzad

“…By using Laplace Adomian decomposition method (LADM), we construct a base function and provide deformation equation of higher order in a simple equation. …”
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An Adaptive Multi-Fidelity Surrogate Model for Uncertainty Propagation Analysis by Wei Xiao, Yingying Shen, Jiao Zhao, Luogeng Lv, Jiangtao Chen, Wei Zhao

“…The results demonstrate that the adaptive model consistently outperforms random sampling methods, highlighting its superiority in terms of accuracy and reliability, providing an efficient and reliable prediction model for uncertainty quantification.…”
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A New Hybrid Model for Underwater Acoustic Signal Prediction by Guohui Li, Wanni Chang, Hong Yang

“…Aiming at the difficulty in underwater acoustic signal sequence prediction, a new hybrid prediction model for underwater acoustic signal is proposed in this paper, which combines the advantages of variational mode decomposition (VMD), artificial intelligence method, and optimization algorithm. …”
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The Riemann Problem for the Blood Flow Model with Body Force Term by Wancheng Sheng, Shufang Xu

“…By a transformation, the system can be transformed into the nonreducible blood flow model. The existence of the simple wave solutions to the nonreducible blood flow model is obtained by the method of characteristic decomposition. …”
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