Coordinated Reactive Power–Voltage Control in Distribution Networks with High-Penetration Photovoltaic Systems Using Adaptive Feature Mode Decomposition by Yutian Fan, Yiqiang Yang, Fan Wu, Han Qiu, Peng Ye, Wan Xu, Yu Zhong, Lingxiong Zhang, Yang Chen

“…This paper proposes a coordinated reactive power and voltage optimization method based on Filtered Multiband Decomposition (FMD). …”
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Wind speed prediction for trains on bridges using enhanced variational mode decomposition assisted feature extraction and physical auxiliary mechanism by Zhilan Zhu, Yuan Jiang, Haicui Wang, Shuoyu Liu

“…This method not only can provide the accurately deterministic prediction, but also can produce the desired probabilistic prediction. …”
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Urban Traffic State Estimation with Online Car-Hailing Data: A Dynamic Tensor-Based Bayesian Probabilistic Decomposition Approach by Wenqi Lu, Ziwei Yi, Dongyu Luo, Yikang Rui, Bin Ran, Jianqing Wu, Tao Li

“…Afterward, the Gibbs sampling method is introduced to calibrate the parameters of the DTBPD models. …”
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Comprehensive thermal properties, kinetic, and thermodynamic analyses of biomass wastes pyrolysis via TGA and Coats-Redfern methodologies by Ocident Bongomin, Charles Nzila, Josphat Igadwa Mwasiagi, Obadiah Maube

“…This study comprehensively analyzes the thermal decomposition characteristics as well as the kinetic and thermodynamic parameters of five biomass wastes, including coffee husk, groundnut shell, macadamia nutshell, rice husk, and tea waste, using Thermogravimetric Analysis (TGA) and the Coats-Redfern method. …”
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Future variation and uncertainty source decomposition in deep learning bias-corrected CMIP6 global extreme precipitation historical simulation by Xiaohua Xiang, Yongxuan Li, Xiaoling Wu, Zhu Liu, Lei Wu, Biqiong Wu, Chuanxin Jin, Zhiqiang Zeng

“…Implementation of CNNs as a BC method could significantly reduce model uncertainty but at the cost of increasing the proportion of scenario uncertainty and internal variability. …”
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A fully automated hybrid approach for processing high-frequency surface settlement data by Changyu Wang, Zude Ding, Annan Zhou, Zekun Zhu

“…However, the lack of standardised data processing procedures results in divergence and inefficiency of the model. This study proposes a novel fully automated hybrid processing method for high-frequency surface settlement data, validated using the automated monitoring dataset in Kunming. …”
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Using a seasonal and trend decomposition algorithm to improve machine learning prediction of inflow from the Yellow River, China, into the sea by Shuo Wang, Shuo Wang, Ke Yang, Ke Yang, Hui Peng, Hui Peng

“…However future data leakage from decomposition items was ignored in many studies. It is necessary to develop the right method to operate time decomposition to avoid future data leakage. …”
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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

“…The proposed method enhances the key frequency-domain features of signals and suppresses the interference of non-stationary noise on model training through adaptive denoising and time–frequency reconstruction. …”
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Graphical Empirical Mode Decomposition–Convolutional Neural Network-Based Expert System for Early Corrosion Detection in Truss-Type Bridges by Alan G. Lujan-Olalde, Angel H. Rangel-Rodriguez, Andrea V. Perez-Sanchez, Martin Valtierra-Rodriguez, Jose M. Machorro-Lopez, Juan P. Amezquita-Sanchez

“…To enhance the computational efficiency of the method without compromising accuracy, different CNN architectures and image sizes are tested to propose a low-complexity model. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…As such, the study proposes a combined prediction model. This model integrates data decomposition, dimensionality reduction, deep learning, and optimization techniques.MethodsThe model uses the variational mode decomposition (VMD) method to break down the ship’s roll motion data into components at different scales. …”
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Exploring brain dysfunction in IBD: A study of EEG-fMRI source imaging based on empirical mode diagram decomposition by Yujie Kang, Wenjie Li, Jidong Lv, Ling Zou, Haifeng Shi, Wenjia Liu

“…Therefore, we propose an electroencephalography (EEG)-functional magnetic resonance imaging (fMRI)source imaging method based on an empirical mode diagram decomposition (EMDD) and performed a synchronous EEG-fMRI source imaging analysis on 21 IBD patients and 11 healthy subjects. …”
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Interrelationships Between Inflammatory Score, Delayed Cerebral Ischemia and Unfavorable Outcome in Patients with aSAH: A Four-Way Decomposition by Zhang P, Zhu H, Li X, Qian Y, Zhu Y, Zhang W, Yan Z, Ni H, Lin Z, Lin X, Li Z, Zhuge Q, Zeng B

“…We also further explore the mediation and interaction of DCI within the chain of events using the four-way effect decomposition.Methods: Machine learning algorithms are used for biomarker selection and constructed the inflammatory score. …”
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Socio-economic inequalities in minimum dietary diversity among Ethiopian children aged 6–23 months: a decomposition analysis by Nigusu Worku, Amare Mesfin Workie, Lamrot Yohannes, Mihret Getnet, Mihret Getnet, Wubshet Debebe Negash, Wubshet Debebe Negash, Adina Yeshambel Belay, Lakew Asmare, Hiwot Tadesse Alemu, Demiss Mulatu Geberu, Melak Jejaw, Kaleb Assegid Demissie, Misganaw Guadie Tiruneh, Asebe Hagos

“…Microsoft Excel and STATA v.14 software were employed to extract, clean, and analyze data. A probit model decomposition analysis was performed. The concentration index (CIX) and curve were used to examine household wealth status and maternal education level inequalities in the MDD.ResultsThe total weighted prevalence of MDD among children under the age of 5 in Ethiopia was 13.5%. …”
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Destripe Any Scale: Effective Stripe Removal Via Multiscale Decomposition Using the Luojia3-02 Stripe-Noise Dataset by Ru Chen, Mi Wang, Yingdong Pi, Ru Wang, Tao Peng, Fan Yang, Rongfan Dai

“…This noise manifests as linear, repetitive patterns that degrade image quality and impede the accurate data analysis. Existing destriping methods, including traditional statistical and frequency-based techniques, optimization-based approaches, and deep-learning models, each exhibit limitations in effectively addressing both small-scale and large-scale stripe noise, particularly in complex and heterogeneous imaging scenarios. …”
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Electrochemical approach for monitoring the catalytic action of immobilized catalase by Peshkov Angel, Shukri Merin, Pimpilova Mariya, Iliev Ilia, Dimcheva Nina

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Global, regional, and national burden of ischemic heart disease attributable to lead exposure, 1990–2021: decomposition, frontier, and projection analysis by Xinyue Wen, Xinyue Wen, Lichun Qiao, Feidan Deng, Jingxuan Zhou, Miaoqian Li, Lin Wang, Huan Deng, Abebe Feyissa Amhare, Jing Han, Yijie Guo

“…Decomposition analysis, frontier analysis, and Bayesian age-period cohort (BAPC) models were applied to assess trends from 1990 to 2021.ResultsIn 2021, deaths and DALYs attributable to lead exposure reached 590,370.03 and 11,854,611.43, respectively, though age-standardized rates (ASRs) declined. …”
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Optimal Forecast Combination for Japanese Tourism Demand by Yongmei Fang, Emmanuel Sirimal Silva, Bo Guan, Hossein Hassani, Saeed Heravi

“…Initially, the time series data were decomposed into high and low frequencies using the Ensemble Empirical Mode Decomposition (EEMD) technique. Following this, Autoregressive Integrated Moving Average (ARIMA), Neural Network (NN), and Support Vector Machine (SVM) forecasting models were applied to each decomposed component individually. …”
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Multi-step prediction of coal mine adit deformation based on time convolutional long short-term memory by Wenli JI, Xin DAN, Chenyang MA, Jing CHAI, Yuyi WU, Fengqi QIU, Wentao LIU, Wulin LEI, Yongliang LIU

“…Based on the application of fiber optic monitoring for adit deformation, A multi-step prediction model is proposed which is built with Ensemble Empirical Mode Decomposition (EEMD) integrated with TCN-LSTM deep learning network for adit deformation. …”
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Optimal Coverage Path Planning for Unmanned Surface Vehicles Using Flexible Formation Tracking Control by Minsung Park, Bo Woo Nam

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Efficiency multi-agent model assisted Moea/D algorithm for optimization design for building taking into account annual energy consumption and annual user discomfort hours by Hua Deng, Kai Zhou

“…Then it introduces a multi-agent model auxiliary mechanism to improve the decomposition based multi-objective evolutionary optimization algorithm, and then solves the multi-objective optimization model for building energy efficiency. …”
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