Performance Portrait Method: Robust Design of Predictive Integral Controller by Mikulas Huba, Pavol Bistak, Jarmila Skrinarova, Damir Vrancic

“…PPM shows that, despite the absence of effective analytical control design methods for such situations, it is possible to obtain high-quality optimal solutions for processes that require working with uncertain models specified by interval parameters, while achieving invariance to changes in uncertain parameters.…”
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A robust multi-model framework for groundwater level prediction: The BFSA-MVMD-GRU-RVM model by Akram Seifi, Sharareh Pourebrahim, Mohammad Ehteram, Hanieh Shabanian

“…The GRU model then extracts crucial information from these decompositions. …”
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Improved and Optimized GNSS-IR Sea Surface Height Retrieval Based on Noise Elimination and Lightweight Airborne Multi-GNSS Multi-UAV Fusion by Naiquan Zheng, Ying Xu, Fuxi Zhao, Mingzhen Xin, Fanlin Yang

“…The inversion accuracy of the improved model is better, which confirms the effectiveness of the improved GNSS-IR model based on intelligent extraction, decomposition and reconstruction of δSNR data. …”
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Comparison of methods for resolving the contributions of local emissions to measured concentrations by T. D. Edwards, Y. K. Wong, C.-H. Jeong, J. M. Wang, Y. Su, G. J. Evans

“…Despite the better performance of regression models, time-series methods still provided reasonable estimates. …”
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On the Global Well-Posedness for a Hyperbolic Model Arising from Chemotaxis Model with Fractional Laplacian Operator by Oussama Melkemi, Mohammed S. Abdo, M.A. Aiyashi, M. Daher Albalwi

“…Several cells and microorganisms, such as bacteria and somatic, have many essential features, one of which can be modeled by the chemotaxis system, which we consider to be our main interest in this article. …”
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Estimating Economic Insights: A Machine Learning Method for Estimating the Shanghai Stock Exchange by Reza Seifi Majdar, Seyed Hadi Seyed Hatami

“…EMD is one of the methods for the decomposition of nonstationary and nonlinear time series data into simpler components. …”
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Hyperspectral Anomaly Detection Using Dual-Branch Network Based on Frequency Domain Learning by Xiaoyi Wang, Jun Du, Qingxuan Lv, Peng Wang, Xianchao Zhang, Jian Cheng, Henry Leung

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Abnormal Load Variation Forecasting in Urban Cities Based on Sample Augmentation and TimesNet by Yiyan Li, Zizhuo Gao, Zhenghao Zhou, Yu Zhang, Zelin Guo, Zheng Yan

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Rolling Bearing Fault Diagnosis Based on Optimized VMD and SSAE by Baoxian Chang, Xing Zhao, Dawei Guo, Siyu Zhao, Jiyou Fei

“…To further enhance the accuracy of identifying rolling bearing faults, a fault diagnosis method is proposed. This method is based on the improved Dung Beetle Optimization (DBO) algorithm for optimizing Variational Mode Decomposition (VMD) combined with Stacked Sparse Autoencoder (SSAE). …”
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Power distribution strategy for a hybrid energy storage system suitable for wind-storage microgrid by LI Yanbo, YANG Kai, CHEN Junshuo, YAO Bobin, LIU Weiyu, WU Qisheng

“…Based on a hybrid energy storage system composed of supercapacitors and batteries, a complementary ensemble empirical mode decomposition method is proposed to smooth the power fluctuations caused by the instability of wind power generation. …”
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The model of automation of university management processes by M. I. Grachev

“…When carrying out the processes of decomposition, abstraction and aggregation, we obtain a mathematical model of a management decision. …”
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Lithium-ion battery RUL prediction based on optimized VMD-SSA-PatchTST algorithm by Pei Tang, Zetao Qiu, Zhongran Yao, Jiahao Pan, Dashuai Cheng, Xiaoyong Gu, Changcheng Sun

“…The Variational Mode Decomposition (VMD) method is then used to break down the raw capacity sequence into a set of intrinsic mode functions. …”
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Research on Sleep Stage Classification of Electroencephalogram Signals Based on CNN and LSTM by Liying Zhu, Qingxin Guan, Yunqing Liu, Jiayue Xu, Sha Ma

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Improved Use of the Full Length of Milling-Tool Flutes in Processes of Air-Contour Milling by César García-Hernández, Juan-Jesús Valdivia-Sánchez, Pedro Ubieto-Artur, Mariano García-Arbués, Anastasios Tzotzis, Juan-José Garde-Barace, Francisco Valdivia-Calvo, José-Luis Huertas-Talón

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A Novel Hybrid Method for Short-Term Power Load Forecasting by Huang Yuansheng, Huang Shenhai, Song Jiayin

“…Finally, the forecasted power load of each component is summed as the final forecasted result of power load. Compared with other methods, the forecasting results of this proposed model applied to the electricity market of Pennsylvania-New Jersey-Maryland (PJM) indicate that the proposed model outperforms other models.…”
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Bearing fault diagnosis based on improved DenseNet for chemical equipment by Wu Huiyong, Jiang Kuan, Wang Yanyu

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Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…This study aims to quantify and evaluate the complexity features of natural gas loads and to develop a multi-step-ahead forecasting model that integrates data decomposition and ensemble deep learning while considering these complexity features. …”
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Correlation between night sweats and season fluctuation in China by Cai Chen, Meng Li, Fulai Peng, Danyang Lv, Xiao Ding, Chongxuan Tian, Weilian Ren, Xiangwei Meng, Tiefeng Sun, Yi Wang, Haitao Du, Fengxia Wu, Wei Li, Ping Wang

“…Meteorological factors, including ambient temperature, humidity, pressure, precipitation and average wind speed in Zhengzhou were obtained from the website https://en.tutiempo.net/climate. A time series decomposition model was used to study the relationship between night sweats and seasonality. …”
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VCAFusion: A Framework for Infrared and Low Light Visible Image Fusion Based on Visual Characteristics Adjustment by Jiawen Li, Zhengzhong Huang, Jiapin Peng, Xiaochuan Zhang, Rongzhu Zhang

“…To further improve fusion quality, we develop an edge-preserving multi-scale decomposition model and a saliency-preserving strategy, ensuring seamless integration of perceptual features. …”
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Research on mapping method of logical carrying network across multiple domains by Min ZHANG, Chun-ming WU, Bin WANG, Ming JIANG

“…In order to solve the mapping problem of logical carrying network across multiple domains,a hierarchical linear program model was presented,which aims to minimize the cost of mapping.Based on this model,a mapping algorithm for logical carrying network across multiple domains was designed using primal decomposition and subgradient optimization technique.The correctness of this method was proved by theoretical analysis,and the validity of the proposed method was assessed by a collection of numerical simulation experiments through the performance of convergence and runtime,as well as mapping request acceptance ratio and revenue in a dynamical network environment.…”
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