Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

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PCL-RC: a parallel cloud resource load prediction model based on feature optimization by Guoxiu Zhang, Xinyi He, Xiaofeng Wang

“…To address the problem of nonlinear load data feature extraction, a feature extraction optimization method that is based on combining an improved random forest method and complete ensemble empirical modal decomposition with adaptive noise is proposed to realize regular decomposition and feature extraction from fluctuating data. …”
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Some Aspects of Thermochemical Decomposition of Peat by Y. A. Losiuk, S. V. Gibric, S. V. Korchinenko

“…The paper considers peculiar features of thermochemical decomposition of peat as a result of quick pyrolysis. …”
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Watermark Based on Singular Value Decomposition by Ali Abdulazeez Mohammed Baqer Qazzaz, Neamah Enad Kadhim

“… Watermarking operation can be defined as a process of embedding special wanted and reversible information in important secure files to protect the ownership or information of the wanted cover file based on the proposed singular value decomposition (SVD) watermark. The proposed method for digital watermark has very huge domain for constructing final number and this mean protecting watermark from conflict. …”
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Unraveling the Atomic Mechanism of the Crystalline Phase‐Dependent Structural Features and Special Spectral Design of α‐, β‐, and Ɛ‐Ga₂O₃ by Xinqing Han, Yong Liu, Yang Li, Miguel L. Crespillo, Eva Zarkadoula, Wenxiang Mu, Peng Liu

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Transformer network for time series prediction via wavelet packet decomposition by Zhichao Wu, Aiye Shi, Yan Ping Tao

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Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition by Ali Nadhim Razzaq, Rozaida Ghazali, Nidhal Khdhair El Abbadi, Hussein Ali Hussein Al Naffakh

“…In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. …”
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Unmasking Machine Learning With Tensor Decomposition: An Illustrative Example for Media and Communication Researchers by Yu Won Oh, Chong Hyun Park

“…By transforming complex datasets into simpler components, tensor decomposition reveals the nuanced relationships among linguistic features. …”
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A Wavelet Decomposition Method for Estimating Soybean Seed Composition with Hyperspectral Data by Aviskar Giri, Vasit Sagan, Haireti Alifu, Abuduwanli Maiwulanjiang, Supria Sarkar, Bishal Roy, Felix B. Fritschi

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Prediction of Gait Neurodegenerative Diseases by Variational Mode Decomposition Using Machine Learning Algorithms by P. Visvanathan, P.M. Durai Raj Vincent

“…Power Spectral Density (PSD) is used to choose best IMF. Feature extraction for the chosen IMF is done with Shannon entropy technique. …”
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Origin centric and part based pose decomposition for 3D human pose estimation by Zhijie Lin, Jinxin Yao, Juan Huang, Jingjing Chen, Yingying Xu, Lu Yang, Lei Zhao, Wei Xing

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Ex-Ante and Ex-Post Decomposition Strategy for Ultra-Short-Term Wind Power Prediction by Peng Lu, Zhuo Li, Lin Ye, Ming Pei, Yingying Zheng, Yongning Zhao

“…However, the strong fluctuation features of wind power make wind power less predictable. …”
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Generalized Riemann-Hilbert-Birkhoff decomposition and a new class of higher grading integrable hierarchies by H. Aratyn, C.P. Constantinidis, J.F. Gomes, T.C. Santiago, A.H. Zimerman

“…We propose a generalized Riemann-Hilbert-Birkhoff decomposition that expands the standard integrable hierarchy formalism in two fundamental ways: it allows for integer powers of Lax matrix components in the flow equations to be increased as compared to conventional models, and it incorporates constant non-zero vacuum (background) solutions.Two additional parameters control these features. …”
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RGB IMAGE BINARY DECOMPOSITION BASED ARABIC AND ENGLISH TEXTS HIDING ALGORITHM WITH 16 CHARACTERS FORMING VIGENERE KEY by Huda Hussein Abed, Salim Muhsin Wadi, Aqeel Sajjad Shaeel

“…The main feature of the proposed algorithm can be summarized as offering security without transferring any information relating to the secret texts with the stego image. …”
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Bridge Damage Identification Using Time-Varying Filtering-Based Empirical Mode Decomposition and Pre-Trained Convolutional Neural Networks by Shenghuan Zeng, Jian Cui, Ding Luo, Naiwei Lu

“…In addition, the principal component analysis visualization results demonstrate that TVFEMD significantly improves the clustering and separability of feature data, providing clearer class boundaries and reducing feature overlap.…”
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EXCHANGE RATE DYNAMICS AND FORECASTING ACCURACY IN EMERGINGECONOMIES: INTEGRATING ENSEMBLE LEARNING MODELS WITH STRUCTURAL TIME SERIES DECOMPOSITION FOR THE USD/ZAR RATE by Agbeyinka Yinka Ibrahim

“…Descriptive statistics and seasonal-trend decomposition reveal notable structural features, including skewness, excess kurtosis, and strong seasonal effects. …”
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Feasibility of Using Wavelet Analysis and Machine Learning Method in Technical Diagnosis of Car Seats by Cezary BARTMAŃSKI, Alicja BRAMORSKA

“…Pattern recognition and machine learning processes were used in the diagnosis. A method of feature extraction (diagnostic symptoms) using wavelet decomposition of acoustic signals was developed. …”
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Exploring Tensor-Based Optimization for Missing EEG Signal Recovery: A Comparative Study of Optimization Methods Across Different Tensor Decomposition Frameworks by Yue Zhang, Huanmin Ge, Chencheng Huang, Xinhua Su

“…This study evaluates various tensor-based methods for reconstructing structured and unstructured missing EEG signals, including recovery methods based on canonical polyadic (CP) decomposition, tensor singular value decomposition (t-SVD), and tucker decomposition. …”
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CUR matrix approximation through convex optimization for feature selection by Kathryn Linehan, Kathryn Linehan, Radu Balan

“…The singular value decomposition (SVD) is commonly used in applications that require a low-rank matrix approximation. …”
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Research and Application of Lifetime Feature Extraction for PCBs Based on Time-Frequency Transforms by YANG Rufei, LIU Haiyang

“…The extracted signal features are subsequently trend-filtered through Spearman correlation analysis to yield lifetime features. …”
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