Elevator Running Fault Monitoring Method Based on Vibration Signal by Mingxing Jia, Xiongfei Gao, Hongru Li, Hali Pang

“…According to the one-dimensional characteristics of the vibration signal, this paper proposes an elevator operation fault monitoring method based on one-dimensional convolutional neural network (1-DCNN). …”
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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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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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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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Presence and detection methods of pseudo-periods in GNSS coordinate time series by Kaichun Yang, Hua Chen, Zhao Li, Jian Wang, Xin Ding, Weiping Jiang

“…Periodic detection of Global Navigation Satellite System (GNSS) coordinate time series is crucial for establishing nonlinear motion models of reference stations. However, uncleaned outliers, offset, and the limited precision of periodic detection methods may introduce pseudo-periodic signals. …”
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Investigation of the Effectiveness of Programs Optimization Methods for Parallel Computing Systems with GPU by A. Yu. Bezruchenko, V. A. Egunov

“…The paper defines the relevance of the task of increasing the efficiency of software, which in this case is understood as reducing the operating time of the designed software in the process of solving computationally complex problems. Method. As an example of such a task, the implementation of the singular value decomposition by the Jacobi method is used. …”
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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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Bearing fault diagnosis based on improved DenseNet for chemical equipment by Wu Huiyong, Jiang Kuan, Wang Yanyu

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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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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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SMART: Structured Missingness Analysis and Reconstruction Technique for credit scoring by Seongil Han, Haemin Jung, Paul D. Yoo

“…Recent advancements have introduced more sophisticated techniques, such as Generative Adversarial Imputation Networks (GAIN), which utilize a generative adversarial network to model data distributions and impute missing values with greater precision than conventional methods. …”
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Hankel Tensor Subspace Representation for Remotely Sensed Image Fusion by Fei Ma, Qiang Qu, Feixia Yang, Guangxian Xu

“…Experimental tests on several real datasets demonstrate that the proposed fusion model significantly achieves better performance in super-resolution reconstruction and noise removal than the representative benchmark methods, which also verifies the validation of Hankel tensor representation and regularization.…”
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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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A new micro HATI second order preserving for transient dynamics by Yvan Le Nôtre, Michael Brun, Clement Grenat, Anthony Gravouil

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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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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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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 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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