A Hybrid Method Combining Variational Mode Decomposition and Deep Neural Networks for Predicting PM2.5 Concentration in China by Senlin Li, Bo Tang, Xiaowu Deng

“…To address this issue, this study introduces a hybrid parallel method (VDPS) that combines variational mode decomposition (VMD) with single deep neural networks for PM2.5 concentration prediction. …”
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Micro-firms’ productivity growth in Poland before and during COVID-19: Do industry and region matter? by Emilia Gosińska, Mariusz Górajski, Magdalena Ulrichs

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Improved decomposition of cloud feedback and corresponding pattern change under uniform surface ocean warming: I. Anomalous mean method by Jing Feng, Jian Ma

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Investigation and Determination of Kinetic Parameters of Sweeteners Based on Steviol Glycosides by Isoconversional Methods by Naienne da Silva Santana, Sergio Neves Monteiro, Tatiana Carestiato da Silva, Michelle Gonçalves Mothé

“…These parameters were assessed using the Friedman and Ozawa–Flynn–Wall isoconversion methods with the NETZSCH Kinetics Neo software and the Model Free package. …”
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Deep Learning-Based Vertical Decomposition of Ionospheric TEC into Layered Electron Density Profiles by Jialiang Zhang, Jianxiang Zhang, Zhou Chen, Jingsong Wang, Cunqun Fan, Yan Guo

“…This study proposes a deep learning-based vertical decomposition model for ionospheric Total Electron Content (TEC), which establishes a nonlinear mapping from macroscale TEC data to vertically layered electron density (Ne) spanning 60–800 km by integrating geomagnetic indices (AE, SYM-H) and solar activity parameters (F10.7). …”
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The VMD Method in Diagnosis of Stator Fault and Stator Current Signal by SHI Xian jiang, LI Wan tao, GAO Qing kang

“…In order to judge the fault state of rolling bearing better, in this paper, the main fault mechanism and characteristics of the bearing are analyzed by using the stator current analysis method. According to the characteristic of the bearing signal, the VMD decomposition method is proposed to extract some weak fault information in current signals, and the method how to decompose the K numbers are given in the VMD decomposition method Under Matlab/Simulink, a simulation model is established to simulate the stator current transformation under normal and fault conditions It is compared with the signals collected by the simulation platform, and the variational modal decomposition method is used to obtain the envelope spectrum Through the comparative analysis between the theoretical simulation and the experimental environment, it is shown that the VMD method can decompose the fault information of the bearing from the current signal, and it is an effective method to deal with the fault of the rolling bearing…”
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Development of the Method for Predicting and Calculating the Operation of Sorption Systems for Cleaning the Generator Gas based on Dolomite Use. Part II by Malko M.V., Vasilevich S.V., Mitrofanov A.V., Mizonov V.E.

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Thermal Decomposition of Calcium Carbonate at Multiple Heating Rates in Different Atmospheres Using the Techniques of TG, DTG, and DSC by Dingxiang Zhuang, Zhengzheng Chen, Bin Sun

“…Calcium carbonate samples were heated linearly at multiple heating rates of 10, 20, 30, and 40 °C/min in the atmospheres of N₂ and 70% N₂ + 30% O₂, respectively. The decomposition kinetics was investigated using a double extrapolation method. …”
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Meta model construction mechanism in SDN architecture by Bin ZHUGE, Hua ZHU, Baoxia WANG, Weiming WANG, Julong LAN

“…Micro service is a new method of modern application architecture,its characteristic is that decomposing the complex applications into discrete,independent service,so that decoupling of applications scheme can be achieved,and the individual service could be developed,deployed and extensioned independently.The change of the application must drive on the change of the underlying network,the architecture of reconfigurable fundamental information communication network aimd to compensate for the network business requirements and network transmission capacity through the network reconfiguration mechanism.A meta model construction mechanism with the SDN architecture for fusion the reconfiguration and software defined network technology was proposed,it aimed to present the services of each layer in the SDN architecture by the form of meta model.And after referencing the AKF scale cube,a kind of meta model building method based on orthogonal decomposition was proposed.Finally,the feasibility of meta model building method based on orthogonal decomposition from the theoretical analysis and development of example was verified.…”
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A Short-Term Wind Speed Forecasting Hybrid Model Based on Empirical Mode Decomposition and Multiple Kernel Learning by Yuanyuan Xu, Genke Yang

“…Extensive experimental results show that, compared with existing machine learning methods, the EMD-MKL model proposed in this paper has better performance in terms of the prediction accuracy evaluation indexes and confidence intervals and shows a better ability to generalize.…”
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Water quality prediction model based on improved long short-term memory neural network and empirical mode decomposition by Feng Lin, Xu Li, Yang Su, Jun Yan

“…This study proposes an improved long short-term memory neural network model for complex time-series water quality data. …”
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Quantum chemistry modeling of the unimolecular decomposition mechanism and substituent effects of pyrazolo-tetrazine: A case study of BITE-101 by Zi-xuan Yang, Shuang-fei Zhu, Hai Duan, Rui-jun Gou, Yang Liu, Shu-hai Zhang

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Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…Parameter standardization employing ASOA, the RSTL decomposition approach, and the conceptual model of LSTM networks are all presented in this research work. …”
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A novel deep learning model for air quality index prediction integrating time series decomposition and intelligent optimization by Guangyao Ma, Kai Xu, Yue Zhang, Lanhe Zhang, Zicheng Chen

“…We then leverage the TimesNet model to capture long-term and periodic patterns within the trend and seasonal series, while employing an improved Transformer (iTransformer) to model the short-term, high-frequency residuals. …”
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Systematic Literature Review for Robust Mixed-Integer Linear Programming Models Using Benders Decomposition in Facility Location Problems by Fadiah Hasna Nadiatul Haq, Diah Chaerani, Anita Triska

“…The robust Mixed-Integer Linear Programming (MILP) model is an approach to address uncertainty in linear optimization involving integer and continuous variables, which can be solved using the Benders Decomposition method. …”
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A multi-channel spatiotemporal SegNet model for short term wind power prediction with sequence decomposition and reconstruction by Xingdou Liu, Liang Zou, Li Zhang, Jiangong Wang, Zhiyun Han, Yong Li

“…This article proposes a multi-channel spatiotemporal SegNet (MCST-SegNet) model that achieves synchronous power prediction for all wind turbines in a wind farm. …”
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Two-step hybrid model for monthly runoff prediction utilizing integrated machine learning algorithms and dual signal decompositions by Shujun Wu, Zengchuan Dong, Sandra M. Guzmán, Gregory Conde, Wenzhuo Wang, Shengnan Zhu, Yiqing Shao, Jinyu Meng

“…The dual decomposition method, integrating seasonal-trend decomposition based on loess (STL) and successive variational mode decomposition (SVMD), demonstrated exceptional efficacy in addressing the complexities of hydrometeorological time series. …”
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Domain knowledge-driven decomposition-based large-scale optimization for ship cabin structures by Puyu JIANG, Jun LIU, Qiangjun LUO, Yuansheng CHENG

“…ObjectivesThis paper proposes a domain knowledge-driven large-scale optimization algorithm for ship cabin structures based on a decomposition optimization framework. MethodsThe proposed algorithm combines domain mechanical knowledge with a general black box optimization algorithm, groups the design variables into location variables and size variables, and decomposes the original problem into a series of low-dimensional subproblems. …”
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A novel multi-class classification method for arrhythmias using Hankel dynamic mode decomposition and long short-term memory networks by Chuchu Liang, Majid Khan Majahar Ali, Lili Wu

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Numerical investigation of mixed convection and viscous dissipation in couple stress nanofluid flow: A merged Adomian decomposition method and Mohand transform by Khader Mohamed M., Adel Mohamed, Messaoudi Mohamed

“…The modified Adomian decomposition method (ADM) is a computational method that simplifies the complex governing equations of the model under study and finds their numerical solutions. …”
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