Estimating Economic Insights: A Machine Learning Method for Estimating the Shanghai Stock Exchange by Reza Seifi Majdar, Seyed Hadi Seyed Hatami

“…EMD is one of the methods for the decomposition of nonstationary and nonlinear time series data into simpler components. …”
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Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder by Shubham Chaudhry, Azzedine Abdedou, Azzeddine Soulaïmani

“…The POD-ANN model utilizes proper orthogonal decomposition to create a reduced-order model, which is then combined with an artificial neural network to establish a surrogate model linking the snapshot matrix to the input parameters. …”
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A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks by Bingbing Yu, Yonggang Wang, Jun Wang, Yuanchu Ma, Wenpeng Li, Weigang Zheng

“…Compared with the basic VMD model, the data decomposition efficiency of the optimized VMD model has been improved by 28.86%. …”
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Application of stochastic methods, wavelet transformations and support vectors for the study of electroencephalogram signals by Veronika V. Tolmanova, Denis A. Andrikov

“…Stochastic methods utilize probabilistic models for modeling random processes and analyzing data statistics. …”
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Underutilized Feature Extraction Methods for Burn Severity Mapping: A Comprehensive Evaluation by Linh Nguyen Van, Giha Lee

“…We applied and compared 13 different FE techniques—including linear and nonlinear methods such as PCA, t-distributed stochastic neighbor embedding (t-SNE), linear discriminant analysis (LDA), Isomap, uniform manifold approximation and projection (UMAP), factor analysis (FA), independent component analysis (ICA), multidimensional scaling (MDS), truncated singular value decomposition (TSVD), non-negative matrix factorization (NMF), locally linear embedding (LLE), spectral embedding (SE), and neighborhood components analysis (NCA). …”
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Wrist Torque Estimation by Combining Motor Unit Discharges With Musculoskeletal Model by Chen Chen, Jiamin Zhao, Yang Yu, Xinjun Sheng, Xiangyang Zhu

“…As neuromusculoskeletal modeling provides a promising alternative, this study proposes a decomposition-based musculoskeletal model for simultaneous and proportional myoelectric control. …”
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Acceleration of Gas Reservoir Simulation Using Proper Orthogonal Decomposition by Yi Wang, Bo Yu, Ye Wang

“…Proper orthogonal decomposition (POD) is introduced to accelerate the reservoir simulation of gas flow in single-continuum porous media via establishing a reduced-order model by POD combined with Galerkin projection. …”
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Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS by Zheng Xiaoxia, Jia Wenhui, Zhou Guowang, Li Jia

“…In order to solve the fault recognition problems caused by a complex signal transfer path,severe noise pollution and the weak fault features,a method for gear based on variational mode decomposition（ VMD）and adaptive neuro-fuzzy inference system（ ANFIS） is proposed. …”
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Hierarchical-Variational Mode Decomposition for Baseline Correction in Electroencephalogram Signals by Shireen Fathima, Maaz Ahmed

“…To address this issue, this article deals with developing a novel scheme of hierarchically decomposing a signal using variational mode decomposition (VMD) in a tree-based model for a given level of the tree for accurate and effective analysis of the EEG signal and research in brain–computer interface (BCI). …”
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Tracing the dual-circulation value chain: Measurement on the embedding characteristics and evidence from China by Yi Ren, Jinniu Zhang, Yuan Tian

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Wavelet Decomposition Prediction for Digital Predistortion of Wideband Power Amplifiers by Shaocheng Peng, Jing You

“…Experimental results demonstrate the effectiveness of our proposed method, achieving the best ACPR and EVM performance on the OpenDPD dataset.…”
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Application of a text mining method in navigation and communication for enhancing maritime safety. by Paulina Hatłas-Sowińska, Leszek Misztal

“…The authors use machine learning methods in the field of text mining and basic and additional properties of ontologies. …”
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Order assignment mechanism based on hierarchical decomposition and element matching by ZHANG Xinyue, LYU Weimin, WEI Dingjiang, YANG Dongsheng

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Decomposition Mechanisms of Lignin-Related Aromatic Monomers in Solution Plasma by Takaki Miyamoto, Jeanielle Amurao, Eiji Minami, Haruo Kawamoto

“…These results provide fundamental insights into lignin decomposition and demonstrate that aqueous solution plasma is a promising method for producing dicarboxylic acids from lignin under mild conditions without catalysts.…”
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STRUCTURAL GLOBAL SENSITIVITY METHOD BASED ON PARTIAL DERIVATIVE WHOLE DOMAIN INTEGRAL by TU LongWei, LIU Jie, LIU GuangZhao, ZHANG Zheng

“…Then,local sensitivity method based on partial derivative was extended to a global sensitivity method by integrating partial derivatives of model variables in variable sapces. …”
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A Three-Component Polarimetric Target Decomposition Algorithm for Grasslands by Baokun Liu, Xiaoqi Lv, Xiujuan Li, Xiangli Yang, Pingping Huang, Weixian Tan, Yongguang Zhai, Yuejuan Chen, Kunpeng Xu

“…Previous polarimetric target decomposition methods have been widely used in forests and buildings and have achieved good results. …”
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Intelligent Malfunction Identification Method in Mechanical Manufacturing Process Based on Multisensor Data by Meng Wang

“…In the process of malfunction identification of keyboard stroke machinery, the accuracy of malfunction identification results is low due to the influence of the identification model. Moreover, a malfunction identification and analysis method for keyboard stroke machinery based on BP optimized by GA is proposed. …”
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A Correction Method for Hardening Artifacts in CT Images Based on Integral Invariance by Yuxin LIU, Jiaotong WEI, Xiaojie ZHAO, Ping CHEN, Jinxiao PAN

“…For imaging experiments with dual-material and multi-material models, compared with directly reconstructed CT images, the hardening artifacts in the reconstructed images were significantly reduced using this method, indicating its effectiveness.…”
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Hybrid precoding method for mmWave massive MIMO systems based on LFM by Haoyi CHEN, Yifan DING, Ying CHENG

“…Analog-digital hybrid precoding is a key technology for millimeter wave massive MIMO systems that reduce hardware costs while balancing system performance.However,the traditional hybrid precoding scheme often needed to find a suitable codebook for precoding,and some codebooks were not easy to obtain or had deviations in actual situations.An analog-digital hybrid precoding method based on latent factor model (LFM) in machine learning without codebook was proposed for this problem.The LFM decomposition and stochastic gradient descent method were used to approximate the designed precoding matrix to the optimal full digital precoding matrix for good performance.The simulation results show that compared with the hybrid precoding design method based on orthogonal matching pursuit (OMP) algorithm,this method not only does not need a codebook,but also has better performance than the hybrid precoding algorithm based on OMP algorithm,which is closer to optimal full digital precoding method.…”
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Interpretable Supervised Muscle Network Decomposition by Multifactorial ANOVA-ICA by Jun-Ichiro Hirayama

“…Existing muscle network decomposition methods do not explicitly disentangle the influence of experimental factors such as task parameters or subject groups, hindering meaningful interpretation. …”
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