Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

“…【Method】The model uses sample entropy reconstruction and the K-means clustering algorithm to optimize the adaptive noise complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) process, generating multiple intrinsic mode functions (IMF). …”
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Behind-the-Fence Generation Forecasting: A Batched Decomposition Framework by Gideon Egharevba, Arne Dankers, Hamidreza Zareipour

“…The batched decomposition method was shown to outperform the benchmarks for both test cases.…”
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A load margin calculation method considering optimized reactive power support by Yuejian Wu, Xiaoming Dong, Tianguang Lu, Shunxiang Yu, Chengfu Wang, Zhengshuo Li

“…Employment of the LU decomposition method allows the CPF predictor coupling with the sensitivity calculation of voltage to reactive power changes (VQ Sensitivity), decreasing the computational burden in identifying the limit-induced bifurcation (LIB). …”
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A spatial bearing fault classification method based on improved APSMOTE-WKMFA by CHEN Chao, YANG Chenhao, XU Haosen, WAN Ouying, HAN Liling

“…Aiming at the problem of poor classification performance of a model for a few classes of fault samples in the case of category imbalance, the spatial bearing fault classification method based on an improved affinity propagation synthetic minority oversampling technique-wavelet kernel marginal Fisher analysis （APSMOTE-WKMFA） was proposed.MethodsFirstly, the geodesic distance was used as the similarity metric for the affinity propagation algorithm, and the synthetic minority oversampling technique （SMOTE） was used to generate samples in the filtered subclusters up to the class balance. …”
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Hybrid Method for Oil Price Prediction Based on Feature Selection and XGBOOST-LSTM by Shucheng Lin, Yue Wang, Haocheng Wei, Xiaoyi Wang, Zhong Wang

“…This study introduces a novel hybrid model framework, distinct from the conventional methods, that integrates influencing factors for oil price prediction. …”
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A method based on clustering fast search for bearing performance degradation assessment by ShengWen Zhou, Li Zhang, Xiaoming Yang, Fan Xu, BaiGang Du, RuiPing Luo, Wenhui Zeng

“…The results show that CFS outperforms other clustering methods and models, including root mean square, kurtosis, Shannon entropy, approximate entropy, and permutation entropy, detecting early-stage degradation more precisely.…”
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An effective method for the abnormal monitoring of stage performance based on visual sensor network by Fuquan Zhang, Gangyi Ding, Lin Xu, Bo Chen, Zuoyong Li

“…As the traditional monitoring method based on sparse description model to realize abnormal behavior of stage performance did not realize the manifold structure during the performance, the behavior characteristics are sparse, and the decomposition has higher volatility, the recognition accuracy of abnormal behavior is low. …”
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Application of decomposition to hyperbolic, parabolic, and elliptic partial differential equations by G. Adomian

“…The decomposition method is applied to examples of hyperbolic, parabolic, and elliptic partial differential equations without use of linearizatlon techniques. …”
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Application of the magnetotelluric method in geothermal exploration in Jianshi county, Hubei province, China by Peng Simeng, Xie Xingbing, Zhang Lianqun, Rao Song, Zhou Lei, Lu Chuyang, Li Yuxi

“…Based on an MT profile in Maotian Township, Jianshi County, this paper processed data from 51 broadband MT measurement points using Fourier transform, Robust estimation, and impedance tensor decomposition techniques. After a detailed analysis of the dimensional characteristics and electrical axes, a 2D electrical structure model from the surface to a depth of 9 km was obtained via topography-based 2D inversion. …”
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Improving Electrical Distance Accuracy for Cable Fault Location Based on the Prony Method by Xiang Ren, Zhiqiang Feng, Kai Zhou, Xueming Zhou, Jianjun Yuan, Yefei Xu, Li Zhang

“…By establishing a frequency-variable coupling model containing the transfer function of the cable with double joint structure, studying the mapping relationship between the cable attenuation constant and the electromagnetic wave velocity, and adopting the Prony estimation method combined with the singular value decomposition noise reduction algorithm to achieve the extraction of the attenuation constant and the decoupling of the segmented wave velocity, thus improving the electrical accuracy of fault location. …”
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An improved MP-NMO correction method based on multiparameter fitting and its application by Xiaohui YANG, Pengfei YU, Jiawei ZHANG

“…Therefore, this study developed an improved MP-NMO correction method based on multiparameter fitting. Specifically, during MP decomposition, cubic polynomial fitting was applied to the amplitude, frequencies, and phases of wavelets from the same reflection interface across different offsets, thus eliminating local anomalies. …”
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Unmanned combat concept based on DoDAF research on systematic description method by LI Yuhao, DU Bo, LIU Yuanyi

“…The decomposition modeling method based on typical elements provide reference for the development and deduction verification of combat concepts, mining of combat capability requirements, and design of combat systems.…”
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Personalized prediction of gait freezing using dynamic mode decomposition by Zhiwen Fu, Congping Lin, Yiwei Zhang

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CEEMDAN-MRAL Transformer Vibration Signal Fault Diagnosis Method Based on FBG by Hong Jiang, Zhichao Wang, Lina Cui, Yihan Zhao

“…The unique MRAL-Net is proposed to extract the spatial features of the signal and analyze the time series dependence of the features to improve the richness of the signal feature scale. This proposed method effectively removes the noise interference. …”
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Implementation of Principal Component Analysis (PCA)/Singular Value Decomposition (SVD) and Neural Networks in Constructing a Reduced-Order Model for Virtual Sensing of Mechanical... by M. A. Melgarejo, A. Pérez, D. Ruiz, A. Casas, F. González, V. González de Lena Alonso

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Study on Distributed Ultrasonic Detection Method of Two-dimensional Gas Temperature Field by LI Shaozhuang, SHI Youan, LU Xiaokang, CHEN Yu, WEI Dong

“…In addressing issues associated with inverse problems, such as the limitations of least squares and algebraic iterative methods, where the number of discrete points cannot exceed the number of propagation paths and the temperature resolution is low, a two-dimensional temperature field reconstruction algorithm based on logarithmic-quadratic (LQ) functions and singular value decomposition (SVD) was developed for autoclave conditions. …”
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Detection Method of Apple Alternaria Leaf Spot Based on Deep-Semi-NMF by FU Zhuojun, HU Zheng, DENG Yangjun, LONG Chenfeng, ZHU Xinghui

“…A comparative analysis was conducted with several other detection methods, including GRX (Reed-Xiaoli detector), LRX (Local Reed-Xiaoli detector), CRD (Collaborative-Representation-Based Detector), LSMAD (LRaSMD-Based Mahalanobis Distance Detector), and the deep learning model Unet. …”
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ALGEBRAIC MODELS OF STRIP LINES IN A MULTILAYER DIELECTRIC MEDIUM by A. N. Kovalenko, A. N. Zhukov

“…This confirms the effectiveness of the constructed models. Numerical results obtained without the procedure for improving the convergence of series for matrix coefficients and results obtained by the projection method using the trigonometric basis are given.…”
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Nighttime foggy image generation algorithm based on semi-analytic model by GUO Fan, LIU Wentao, YANG Jianan, TANG Jin

“…Then, an intrinsic image decomposition method was used to decompose the night image into illuminance map and reflection map to obtain the relevant parameters of the semi-analytical model. …”
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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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