Multiphysical model of CMUT array based on modal decomposition and the Rayleigh integral by A.E. Biriukov, A.M. Korsunsky

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An Hourly Prediction Model of Relativistic Electrons Based on Empirical Mode Decomposition by Yedong Qian, Jianwei Yang, Hua Zhang, Chao Shen, Yewen Wu

“…Moreover, we use this method to forecast daily fluence to validate empirical mode decomposition. …”
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Mine pressure prediction based on empirical mode decomposition linear model by Yuwei ZHU, Pengfei WANG, Huixian WANG, Qiangqiang NIU, Liang XIN

“…Unlike most fixed-length single-feature mine pressure prediction models, this model first introduces the Empirical Mode Decomposition (EMD) method to separate periodic and trend components from the mine pressure signals. …”
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Bolt Anchorage Quality Levels Classification Method Based on HO‐VMD‐CNN‐BiLSTM by Fan Kesong, Zhang Can, Liu Shaowei, Feng Mengyin, Yan Ao, Fu Mengxiong, He Deyin, Nie Zhibin

“…In this paper, a new model named HO‐VMD‐CNN‐BiLSTM is proposed to optimize the accuracy of signal decomposition and quality classification. …”
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An Improved Three-Component Decomposition Method for <inline-formula><tex-math notation="LaTeX">$\pi$</tex-math></inline-formula>/4 Mode Compact PolInSAR Using Refined Volume Scattering Models by Yu Wang, Weidong Yu, Daqing Ge, Bin Liu, Chunle Wang, Ling Zhang, Man Li

“…In this article, an improved three-component decomposition method for <inline-formula><tex-math notation="LaTeX">$\pi /4$</tex-math></inline-formula> compact polarimetric synthetic aperture radar Interferometry (PolInSAR) is proposed to interpret the scattering mechanisms of various terrain types. …”
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A Short-Term Load Interval Forecasting Method Based on EEMD-SE and PSO-KELM by Lin ZHANG, Jichun LIU

“…This paper presents a short-term load interval forecasting method based on EEMD-SE and PSO-KELM. Firstly, the ensemble empirical mode decomposition (EEMD) is used to decompose the original load series into a series of subseries. …”
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Maximum Accommodation Capacity Decomposition of Distributed Renewable Power Generation Considering Multi-Level Distribution Network by Donglei SUN, Yi SUN, Rui LIU, Pengkai SUN, Yumin ZHANG

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Methodology-Dependent Reversals in Root Decomposition: Divergent Regulation by Forest Gap and Root Order in <i>Pinus massoniana</i> by Haifeng Yin, Jie Zeng, Size Liu, Yu Su, Anwei Yu, Xianwei Li

“…The results showed the following: (1) Root decomposition was significantly accelerated by the in situ soil litterbag method (ISLM) versus the traditional litterbag method (LM) (decomposition rate (<i>k</i>) = 0.459 vs. 0.188), reducing the 95% decomposition time (<i>T_0.95</i>) by nearly nine years (6.53 years vs. 15.95 years). …”
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Research on a Joint Extraction Method of Track Circuit Entities and Relations Integrating Global Pointer and Tensor Learning by Yanrui Chen, Guangwu Chen, Peng Li

“…Next, the Tucker decomposition method is utilized to capture the semantic correlations between relations, and an Efficient Global Pointer is employed to globally predict the start and end positions of subject and object entities, incorporating relative position information through rotary position embedding (RoPE). …”
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A Quality Control Method based on Combination Deep Learning for Measurement Data of Complex Mountain Wind Farm by Runjin YAO, Shuaibing CHENG, Qianqian ZHAO, Wenlong LI, Dong QIAN

“…Mountainous winds exhibit strong intermittent， fluctuating， and non-stationary characteristics due to the influence of terrain， resulting in poor observation quality， which makes conventional quality control methods unable to effectively improve their observation quality.To address this issue， a quality control method （VCG） based on variational mode decomposition， convolutional neural networks， and deep learning of gated cyclic units is constructed， and a particle swarm optimization strategy and wind power reconstruction model are introduced to comprehensively improve the quality of observation data.To verify the effectiveness of this method， 10 minute wind speed and direction data of target wind turbines in six complex mountainous wind farms in Jiangxi Ganzhou， Sichuan Guangyuan， Anhui Wuhu， Hubei Huangshi， Henan Pingdingshan， and Guangxi Hezhou in 2016 was quality controlled by VCG and compared with single machine learning method， spatial regression method （SRT）， and inverse distance weighting method （IDW）.The results indicate that VCG method is suitable for quality control of observed wind data in mountainous wind farms， and has a higher error detection rate for suspicious data compared to conventional methods； The controlled data can better restore the observed background field and have a lower error rate when applied to the power generation evaluation business of wind farms； And it has the characteristics of strong terrain adaptability.…”
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MODELS AND METHODS FOR SYNTHESIS OF MANUFACTURING PROCESS STRUCTURE FOR MACHINING AT FLOW LINE OF STATIONARY MACHINES by N. N. Guschinsky, O. Battaia, A. Dolgui

“…A problem of design of a flow line composed of stationary machines is considered. Mathematical models and methods for synthesis of manufacturing process structure are proposed. …”
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A New Method for Estimating the Input-Energy of MDOF Structures by D. Davarnia, B. Farahmand Azar

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A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer by Xuebin Huang, Anfeng Xu, Hongbing Liu, Bingcheng Ye

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Model Parameter Estimation Method on Multichannel Structural Response from Turbulence Flutter Test by Shiqiang Duan, Hua Zheng, Ziwei Zhang, Jianzhu Wang, Guanyu Fang

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Transformer Failure Rate Model Based on DDgPCE Method and Oil Chromatography Datadd by CHEN Li juan, WU Jian jun, WANG Gang, DAI Zi kuo, LIU Zhen dong, TAN Yu hua, ZHOU Yul ong

“…Thirdly, considering the health status and service life of transformer, the distribution model of transformer failure rate is established by data-driven generalized polynomial chaos method. …”
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A Mechanical Fault Diagnosis Method for On-Load Tap Changers Based on GOA-Optimized FMD and Transformer by Ruifeng Wei, Zhenjiang Chen, Qingbo Wang, Yongsheng Duan, Hui Wang, Feiming Jiang, Daoyuan Liu, Xiaolong Wang

“…To achieve this, a novel hybrid method is proposed that integrates the Gazelle Optimization Algorithm (GOA), Feature Mode Decomposition (FMD), and a Transformer-based classification model. …”
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Short Term Photovoltaic Power Combination Prediction Method Based on Similar Day Selection and Data Reconstruction by Qingbin CHEN, Genghuang YANG, Liqing GENG, Juan SU, Jingsheng SUN

“…Then, the variational mode decomposition method is used to decompose the photovoltaic power into several subsequences, and the permutation entropy is calculated and reconstructed into trend, low-frequency, and high-frequency terms. …”
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Methods of Forensic Linguistics by V. O. Kuznetsov

“…He also gives a brief description of the key methods: observation, description, experiment, modeling, definitional analysis, synonymic paraphrasing, semantic decomposition, contextual analysis, analysis of the modal organization of the sentence, semantic and pragmatic analysis of the speech act.…”
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Enhancing multi-temporal drought forecasting accuracy for Iran: Integrating an innovative hidden pattern identifier, recursive feature elimination, and explainable ensemble learnin... by Mahnoosh Moghaddasi, Mansour Moradi, Mehdi Mohammadi Ghaleni, Mehdi Jamei

“…Additionally, the effectiveness of the suggested model (HPFE-ETR) was assessed and contrasted with two common methods, Time-Varying Filter-based Empirical Mode Decomposition (TVF-EMD) and Variational Mode Decomposition (VMD), both of which were combined with ETR. …”
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Image Characteristic-Guided Learning Method for Remote-Sensing Image Inpainting by Ying Zhou, Xiang Gao, Xinrong Wu, Fan Wang, Weipeng Jing, Xiaopeng Hu

“…Additionally, IGLL incorporates mathematical constraints into deep-learning models. A singular value decomposition (SVD) loss item is proposed to model the low-rankness characteristic, and it constrains feature consistency. …”
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