Motor Fault Diagnosis Under Strong Background Noise Based on Parameter-Optimized Feature Mode Decomposition and Spatial–Temporal Features Fusion by Jingcan Wang, Yiping Yuan, Fangqi Shen, Caifeng Chen

Subjects: “…parameter-optimized feature mode decomposition…”
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Transmission Tower Tilt State Recognition Based on Parameter Optimization of VMD-SVD and LSTM by Long ZHAO, Guanru WEN, Zhicheng LIU, Peng YUAN, Xinsheng DONG

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Performance analysis and parameter optimization of microchannel heat sink with porous-solid composite ribs by Chunjie Liu, Shixin Xing, Wenrui Wang, Dinghua Hu

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Short-Term Power Load Forecasting Using Adaptive Mode Decomposition and Improved Least Squares Support Vector Machine by Wenjie Guo, Jie Liu, Jun Ma, Zheng Lan

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A multi-modal feature combination mechanism for identification of harmonic load in distribution networks based on artificial intelligence models by Renzeng Yang, Shuang Peng, Gang Yao

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Intelligent Fault Severity Detection of Rotating Machines Based on VMD-WVD and Parameter-Optimized DBN by Ning Jia, Yao Cheng, Youyuan Tian, Feiyu Yang

“…The fitness function in the parameter optimization process is the network’s root mean square error (RMSE). …”
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Research on axle-box bearing fault feature extraction algorithm based on simulation test and BOA-VMD by ZHANG Dongxing, YANG Gang, ZHOU Ao, QIN Limu, WEI Yuqian, YAN Lei

“…Aiming at the problem that axle-box bearing faults are difficult to find during the operation of urban rail trains, a bearing fault feature extraction based on variational mode decomposition (VMD) parameter optimization using butterfly optimization algorithm (BOA) was proposed. …”
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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

“…The proposed research work is developed using the gait neurodegenerative data composed of gait signals collected from physionet database. The composite non stationary and nonlinear gait signals are decomposed into different modes of Intrinsic Mode Function (IMF) using Variational Mode Decomposition (VMD). …”
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Application of KTA-KELM in Fault Diagnosis of Rolling Bearing by Zhuo Wang, Wenjun Zhao, Tao Ma, Zhijun Li, Bo Qin

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Parameter optimization for multistage horizontal well fracturing based on multi-cluster perforation for deep coal measure gas: A case study of the Jurassic Baijiahai area in the Ju... by Bo WANG, Chenghong JIN, Jiang LIU, Zhiwei WANG, Shenjian LI, Mao SHENG

“…As a result, existing fracturing experience cannot be directly applied, highlighting the investigation of fracturing parameter optimization tailored for deep CMG production.MethodsFocusing on deep CMG reservoirs in the Baijiahai area within the Junggar Basin, this study constructed a model of multistage horizontal well fracturing based on multi-cluster perforation for a composite geological structure composed of a roof, a floor, gangue, and coals. …”
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Bearing fault diagnosis for high-speed train based on improved VMD and APSO-SVM by ZHANG Qingsong, ZHANG Bing, QIN Yi

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A Novel Method for Mechanical Fault Diagnosis Based on Variational Mode Decomposition and Multikernel Support Vector Machine by Zhongliang Lv, Baoping Tang, Yi Zhou, Chuande Zhou

“…The global optimal parameter vector of MKSVM can be rapidly identified by IGA parameter optimization. The experiments of mechanical faults show that, compared to traditional fault diagnosis models, the proposed method significantly increases the diagnosis accuracy of mechanical faults and enhances the generalization of its application.…”
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A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Hence, a novel hybrid model is provided, incorporating singular value decomposition (SVD) in conjunction with kernel-based ridge regression (SKRidge), multivariate variational mode decomposition (MVMD), and the light gradient boosting machine (LGBM) as a feature selection method, along with the Runge–Kutta optimization (RUN) algorithm for parameter optimization. …”
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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method and fuzzy entropy (FE) with the new and highly efficient Runge–Kuta optimizer (RUN), adaptive parameter optimization for the support vector machine (SVM) and radial basis function neural network (RBFNN) algorithms was achieved. …”
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Research on Bearing Fault Diagnosis Method Based on MESO-TCN by Ruibin Gao, Jing Zhu, Yifan Wu, Kaiwen Xiao, Yang Shen

“…The method integrates feature filtering, network modeling, and parameter optimization into a unified diagnostic framework. …”
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Short-Term Load Forecasting Based on EEMD-WOA-LSTM Combination Model by Lei Shao, Quanjie Guo, Chao Li, Ji Li, Huilong Yan

“…Each feature component is input into the bionic optimized combination model for prediction. …”
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GPPK4PCM: pest classification model integrating growth period prior knowledge by Jianhua Zheng, Junde Lu, Yusha Fu, Ruolin Zhao, Jinfang Liu, Zhaoxi Luo, Zhijie Luo

“…The model is composed of three sub-modules where: i) A deep learning network first identifies the growth periods of pests, and this prior knowledge is then used to guide the text encoder of the CLIP pre-trained model in generating period-specific textual features. ii) A parallel deep learning network extracts visual features from pest images. iii) An efficient low-rank multimodal fusion module integrates textual and visual features through parameter-optimized tensor decomposition, significantly improving classification accuracy across pest developmental phases. …”
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An Integrated Mechanical Fault Diagnosis Framework Using Improved GOOSE-VMD, RobustICA, and CYCBD by Jingzong Yang, Xuefeng Li

“…Addressing the limitations of conventional methods in adaptive parameter optimization and weak feature enhancement, this paper proposes an innovative diagnostic framework integrating Improved Goose optimized Variational Mode Decomposition (IGOOSE-VMD), RobustICA, and CYCBD. …”
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A Hybrid Fault Diagnosis Model for Rolling Bearing With Optimized VMD and Fuzzy Dispersion Entropy by Xin Xia, Xiaolu Wang, Weilin Chen

“…To improve the efficiency of feature extraction and fault diagnosis, a hybrid model based on optimized variational mode decomposition (VMD), fuzzy dispersion entropy (FDE), and a support vector machine (SVM) is proposed. …”
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Research on the Estimation Model of Electrical Parameters of Silver-Based Contacts Based on Surface Morphology by Chao Wang, Xiancheng Wang, Chengjun Guo

“…Existing research on the correlation of morphological–electrical performance is based solely on empirical models from traditional visual inspections and only considers the impact of visually observable macro-textural features on electrical performance. …”
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