A novel multi-class classification method for arrhythmias using Hankel dynamic mode decomposition and long short-term memory networks by Chuchu Liang, Majid Khan Majahar Ali, Lili Wu

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Numerical investigation of mixed convection and viscous dissipation in couple stress nanofluid flow: A merged Adomian decomposition method and Mohand transform by Khader Mohamed M., Adel Mohamed, Messaoudi Mohamed

“…The modified Adomian decomposition method (ADM) is a computational method that simplifies the complex governing equations of the model under study and finds their numerical solutions. …”
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Multi-Dimensional Parameter-Estimation Method for a Spatial Target Based on the Micro-Range Decomposition of a High-Resolution Range Profile by Xing Wang, Degui Yang, Zhichen Zhao

“…To address these challenges, this paper proposes a multi-dimensional parameter-estimation method for spatial targets based on micro-range decomposition. …”
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Ensemble empirical mode decomposition-based preprocessing method with Multi-LSTM for time series forecasting: a case study for hog prices by Lianlian Fu, Xinsheng Ding, Yuehui Ding

“…Existing papers have neglected the benefits of decomposition and instead directly utilise models to predict hog prices by capturing raw data. …”
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Decomposition and Conceptualization to Support System Dynamics Behavior Modeling by Fiona Tulinayo, Theo van der Weide, Patrick van Bommel

“…In this article, we use the decomposition mechanism to better conceptualize and understand the System Dynamics (SD) model behavior, and show how using a natural language based domain modeling method (Object-Role Modeling, ORM) helps in dealing with complex SD models. …”
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TNN-STME: A Matrix Decomposition Method for SAR Ship Real-Time Detection Using 2-D Asymmetric Resolution Mode by Chaoyue Liu, Yunkai Deng, Zhimin Zhang, Huaitao Fan, Heng Zhang, Xiangyang Qi, Wei Wang

“…The experiments show that the proposed method can realize the sparse target matrix extraction (STME) through matrix decomposition. …”
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Epidemiological analysis of Lassa fever control using novel mathematical modeling and a dual-dosage vaccination approach by Akeem Olarewaju Yunus, Morufu Oyedunsi Olayiwola

“…Compared to conventional integer-order methods, this study presents an improved analysis of disease dynamics, including vaccine efficacy, by utilizing fractional-order models and the Laplace Adomian Decomposition methods. …”
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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

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A Method of Sample Models of Program Construction in Terms of Petri Nets by D. I. Kharitonov, E. A. Golenkov, G. V. Tarasov, D. V. Leontyev

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Short-term forecasting method for net load considering the impact of high proportion of distributed renewable energy by Yuhang Song, Haibo Zhang, Hanru Wu, Joseph Ndonji

“…The model first employs a neural network-based sequence-to-point learning non-intrusive load decomposition method to decompose the net load data into constituent components with different characteristics. …”
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Sequential image deep learning-based Wi-Fi human activity recognition method by Qizhen ZHOU, Jianchun XING, Qiliang YANG, Deshuai HAN

“…For the problems existing in most of the researches,such as weak anti-noise ability,incompatible signal size and insufficient feature extraction of deep-learning-based Wi-Fi human activity recognition,a kind of sequential image deep learning-based recognition method was proposed.Based on the idea of sequential image deep learning,a series of image frames were reconstructed from time-varied Wi-Fi signal to ensure the consistency of input size.In addition,a low-rank decomposition method was innovatively designed to separate low-rank activity information merged in noises.Finally,a deep model combining temporal stream and spatial stream was proposed to automatically capture the spatiotemporal features from length-varied image sequences.The proposed method was extensively tested in WiAR dataset and self collected dataset.The experimental results show the proposed method could achieve the accuracy of 0.94 and 0.96,which indicate its high-accuracy performance and robustness in pervasive environments.…”
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A Novel Method for 3-D Building Structure Determination in Through-the-Wall Radar by Qichang Guo, Xingdong Liang, Yanlei Li

“…Moreover, in order to keep the global correlation of the image in the case of the errors, the tensor Tucker decomposition is adopted. The performance of this method is discussed in the simulation and real radar data results. …”
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Electricity pinch analysis method for flexibility supply-demand matching in power systems by Yaling Mao, Tiejiang Yuan, Xueqin Tian, Yue Teng

“…Leveraging the theoretical framework of pinch technology from process engineering, this paper proposes an Electricity Pinch Analysis (EPA) method for flexibility assessment. First, the net-load profile is decomposed by successive variational mode decomposition (SVMD) optimized with the Red-billed Blue Magpie Optimization (RBMO) algorithm to construct a flexibility demand model. …”
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Statistics release and privacy protection method of location big data based on deep learning by Yan YAN, Yiming CONG, Mahmood Adnan, Quanzheng SHENG

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A Clustering-Based Dimensionality Reduction Method Guided by POD Structures and Its Application to Convective Flow Problems by Qingyang Yuan, Bo Zhang

Subjects: “…POD (proper orthogonal decomposition)…”
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Calculation Method and Characteristic Analysis for Fault Current of Permanent Magnet Direct-Drive Wind Power System considering Positive and Negative Sequence Decomposition by Botong Li, Qing Zhong, Weijie Wen, Bin Li, Xiaolong Chen

“…In view of the fact that the influence of positive and negative sequence decomposition, which is widely used in positive and negative sequence decoupling control in control system, on the fault current calculation process is not deeply considered in the existing transient analysis methods of permanent magnet direct-drive wind farm short circuit current, this paper proposes a transient short circuit current calculation model that takes into account positive and negative sequence decomposition. …”
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Analysis on hydrodynamic interaction of two floating bodies with different dimensions using a hybrid two-way coupled field-domain decomposition method by Fujian LI, Xueqin LIU, Dan LI, Wei MENG, Zhuang KANG

“…ConclusionsThis study employs the hybrid two-way coupled field-domain decomposition method to validate the hydrodynamic interference model between two floating bodies. …”
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Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…<p>This paper presents a brand-new hybrid solar photovoltaic (PV) power forecasting model called empirical mode decomposition (EMD)-particle swarm optimisation (PSO)-adaptive neuro-fuzzy inference system (ANFIS). …”
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A 4D-EnKF Method via a Modified Cholesky Decomposition and Line Search Optimization for Non-Linear Data Assimilation by Elías D. Nino-Ruiz, Jairo Diaz-Rodriguez

“…This paper introduces an efficient approach for implementing the Four-Dimensional Variational Ensemble Kalman Filter (4D-EnKF) for non-linear data assimilation, leveraging a modified Cholesky decomposition (4D-EnKF-MC). In this method, control spaces at observation times are represented by full-rank square root approximations of background error covariance matrices, derived using the modified Cholesky decomposition. …”
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Combined wideband speech enhancement method based on statistical model and EMD by Xuan ZHOU, Chang-chun BAO, Bing-yin XIA

“…A combined wideband speech enhancement method based on statistical model and empirical mode decomposition (EMD) was proposed.First,statistical model was used to eliminate the main noise component in noisy speech.Then,the residual noise was further suppressed by a post-processing module which is a speech enhancement algorithm with voice activity detection (VAD) based on EMD.The advantages of the two methods were combined effectively.The performance of the proposed method was evaluated under the standard of ITU-T G160.The experimental results indicate that the algorithm is more effective for improving the SNR in the different noise environments than classical statistical model approach.Meanwhile,in low SNR conditions,musical noise is reduced effectively,and the speech sounds more comfortable.…”
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