A source-load collaborative stochastic optimization method considering the electricity price uncertainty and industrial load peak regulation compensation benefit by Xiaoyu Yue, Lijun Fu, Siyang Liao, Jian Xu, Deping Ke, Huiji Wang, Shuaishuai Feng, Jiaquan Yang, Xuehao He

“…This paper combines the complete ensemble empirical mode decomposition adaptive noise (CEEMDAN), whale optimization algorithm (WOA), and long short-term memory network (LSTM) to propose a CEEMDAN-WOA-LSTM prediction model for electricity price scenarios. …”
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Optimal DMD Koopman Data-Driven Control of a Worm Robot by Mehran Rahmani, Sangram Redkar

“…The dynamic mode decomposition (DMD) method is used to generate the Koopman operator. …”
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Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland by Tonglin Fu, Dong Wang, Jing Jin

“…However, developing highly accurate and universal data- driven models using time-series analysis methods to achieve precise evaporation estimation remains a challenging. …”
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Lateral vibration estimation of an elevator rope by sequential modal decomposition of elevator rope displacement observed near the traction sheave by Daisuke TAINAKA, Nanako MIURA, Keito SUMIDA, Arata MASUDA

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Forecasting Significant Wave Height Intervals Along China’s Coast Based on Hybrid Modal Decomposition and CNN-BiLSTM by Kairong Xie, Tong Zhang

“…This study proposes a deep learning method based on buoy datasets collected from four research locations in China’s offshore waters over three years (2021–2023, 3-hourly). …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…By combining statistical and deep learning methods, hybrid models incorporating VMD offer a comprehensive solution for accurate temperature prediction, with implications for climate modeling and environmental monitoring.…”
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Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network by Rihab Abdullah Jaber Al Hamadani, Mahdi Mosleh, Ali Hashim Abbas Al-Sallami, Rasool Sadeghi

“…This study proposes an effective deep learning-based traffic prediction technique using BiLSTM (Bidirectional Long Short-Term Memory). The proposed method begins with preprocessing using K-SVD (K-means Singular Value Decomposition) to reduce dimensionality and enhance data representation. …”
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Multivariate decomposition of shift toward public facilities for inpatient care in rural India: evidence from National Sample Survey by Sandeep Sharma, E Lokesh Kumar, Atul Kotwal

“…This study conducted a decomposition analysis to identify the underlying causes that contributed to this increase in public facility utilization.Materials and methodsThe study used the latest available unit-level data from the 2014 and 2017–2018 NSS Health Survey. …”
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Enhancing the Opportunistic Bone Status Assessment Using Radiomics Based on Dual-Energy Spectral CT Material Decomposition Images by Qiye Cheng, Jingyi Zhang, Mengting Hu, Shigeng Wang, Yijun Liu, Jianying Li, Wei Wei

“…Conclusions: Bone status assessment can be accurately conducted using density values from HAP (Water), HAP (Fat), Ca (Water), and Ca (Fat) MD images. However, radiomics models derived from MD images surpass traditional density measurement methods in evaluating bone status, highlighting their superior diagnostic potential.…”
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Decomposition analysis of public health service utilization and health disparities among urban and rural older adult migrants in China by Bo Dong, MengHan Jiang, Jing Zong

“…Finally, the Blinder–Oaxaca decomposition method was used to quantify the extent to which various factors contributed to urban–rural disparities in health service utilization and health outcomes.ResultsRural older adult migrants exhibited slightly higher utilization rates of public health services—health education, health records, and family doctor contracting—compared to their urban counterparts. …”
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Advancements in energetic metal-organic frameworks, alkali and alkaline earth metal salts, and transition metal complexes: Predictive models for detonation velocity, heat, and pres... by Mohammad Hossein Keshavarz, Nasser Hassanzadeh, Mohammad Jafari

“…The new model enhances predictive reliability for detonation velocities, aligning more closely with experimental results, as evidenced by a root mean square error (RMSE) of 0.68 km/s compared to 1.12 km/s for existing methods. …”
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Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition by Zeinab Hassani, Davud Mohammadpur, Hossein Safari

“…To address class imbalance, resampling methods are applied. LSTM and DLSTM models are trained on sequences of peak fluxes and waiting times from irregular time series, while LSTM and DLSTM, integrated with an ensemble approach, are applied to sliding windows of regularized time series with a 3 hr interval. …”
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Fault Diagnosis Method of Plunger Pump Based on Meta-Learning and Improved Multi-Channel Convolutional Neural Network Under Small Sample Condition by Xiwang Yang, Jiancheng Ma, Hongjun Hu, Jinying Huang, Licheng Jing

“…The signal is first preprocessed using adaptive chirp mode decomposition (ACMD) methods. A multi-channel input structure is then employed to process the multidimensional signal information after preprocessing. …”
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A novel seismic inversion method based on multiple attributes and machine learning for hydrocarbon reservoir prediction in Bohai Bay Basin, Eastern China by Zongbin Liu, Jianmin Zhu, Bo Tian, Rui Zhang, Yongheng Fu, Yuan Liu, Lixin Wang

“…Compared to traditional seismic inversion methods, our method requires less data. This approach may find a wider application, especially at offshore oilfields with few wells data and low quality seismic data.…”
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Evaluating and enhancing the service capacity of secondary public hospitals in urban China: a multi-method empirical analysis based on Guangzhou (2019–2023) by Baoling Wu, Baoling Wu, Wenbo Wu, Xi Wang, Weizhang Huang, Zhenni Luo, Jifeng Li

“…This study aims to systematically evaluate the evolution and spatial dynamics of service capacity among secondary general public hospitals in Guangzhou, offering empirical evidence to support capacity improvement and policy optimization.MethodsA composite evaluation framework was constructed across three dimensions: medical quality, operational efficiency, and sustainability. …”
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Bridge Deck Modal Parameters Identification Using Traffic Loads by Meisam Talebi, Zahra Tabrizian, Gholamreza Ghodrati Amiri

“…Structural Health Monitoring (SHM) has gained significant importance in recent decades, with various methods developed to detect structural damage. Many non-destructive damage detection techniques are based on vibration response analysis, where changes in modal parameters provide insights into the condition of the structure. …”
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Fault Diagnosis of Gearboxes Based on AO-VMD and IAO-SVM by Wang Bo, Nan Xinyuan

“…Aiming at the problems of improving the adaptability of variational mode decomposition (VMD) and in order to optimize the intrinsic mode function (IMF) and multi-fault classification, a gearbox fault diagnosis method is proposed, with which the Aquila optimizer (AO) optimizes VMD, the comprehensive evaluation model optimizes IMF, and improves the Aquila optimizer optimization support vector machine (IAO-SVM). …”
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Visual Servo Tracking Control and Scene Depth Identification of Mobile Robots with Velocity Saturation Constraints by Qiaomei Zhang, Baoquan Li, Fuyun Sun

“…By analyzing the kinematic model of the robot system and employing the homography decomposition technique, measurable signals are obtained to develop a visual tracking error model for non-holonomic mobile robots. …”
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Decomposing socioeconomic inequalities in contraceptive use among Kurdish women: a cross-sectional analysis of the ravansar cohort study by Ali Kazemi-Karyani, Sina Ahmadi, Jafar Yahyavi Dizaj, Farid Najafi, Moslem Soofi

“…The Wagstaff normalized concentration index was employed to assess income-related inequalities. Two separate models were developed to analyze the contributing factors for the use of temporary contraceptive methods and tubectomy. …”
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A study of grain boundary precipitation of nano-scale Cu-rich phase in polycrystalline Fe–Cu binary alloys using a phase-field method by Mingguang Wei, Tongguang Zhai, Kang Wang

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