Multi-Source Attention U-Net: A Novel Deep Learning Framework for the Land Use and Soil Salinization Classification of Keriya Oasis in China with RADARSAT-2 and Landsat-8 Data by Yang Xiang, Ilyas Nurmemet, Xiaobo Lv, Xinru Yu, Aoxiang Gu, Aihepa Aihaiti, Shiqin Li

“…Moreover, the MS + SAR MSA-U-Net, in comparison to traditional machine learning methods and the baseline model, improved the OA and Kappa coefficient by 8.24% to 12.55% and 0.08 to 0.15, respectively. …”
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The global, regional, and national brain and CNS cancers burden and trends from 1990 to 2021 by Jian Zhou, Long Gu, Fengling Du, Chun Li, Fan Zhang, Xianhui Zhang, Jinwei Pang, Bingqing Xie, Xiangyu Wang, Jianhua Peng, Yong Jiang

“…The estimated annual percentage change (EAPC) and joinpoint regression analysis were employed to assess temporal trends in cancer burden metrics from 1990 to 2021. Das Gupta’s decomposition method was used to quantify the relative contributions of population growth, aging and epidemiological changes on the cancer burden. …”
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Fast binary logistic regression by Nurdan Ayse Saran, Fatih Nar

“…This study presents a novel numerical approach that improves the training efficiency of binary logistic regression, a popular statistical model in the machine learning community. Our method achieves training times an order of magnitude faster than traditional logistic regression by employing a novel Soft-Plus approximation, which enables reformulation of logistic regression parameter estimation into matrix-vector form. …”
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Planning of Distributed Energy Storage in Distribution Networks Considering Operational Efficacy Under Typhoon Weather by YIN Jianbing, HUO Jiali, YU Dan, CHEN Lin, SONG Kexuan, LI Zhiyi

“…The method solves the dimension disaster of the model considering massive scenes Finally, the IEEE 33 bus system is taken as an example to verify the effectiveness of the proposed model and the rapidity of the solution algorithm.…”
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An improved GRU method for slope stress prediction by Lichun Bai, Ronghui Zhao, Sen Lin, Zishu Chai, Xuan Wang

“…In order to address the aforementioned issues, the present paper proposes an intelligent prediction model based on Variational Mode Decomposition (VMD) and Dung Beetle Optimization (DBO), combined with an improved Gated Recurrent Unit (GRU), which is hereby referred to as the VMD-DBO-GRU-A model. …”
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Research on blindsight technology for object recognition and attitude determination based on tactile pressure analysis by Chen Li, Li HuiJun, Song Aiguo

“…The paper first constructs a contact surface deformation model for classic button operations and grasping operations in power systems, based on Hertz contact and elastoplastic unloading theories, laying the theoretical foundation for the vector mechanics decomposition of the contact surface. …”
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Study of the possibility of using an artificial neural network to recognize and assess the contribution of individual radionuclides to the total beta spectrum by V. S. Repin

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A Multi-Index Fusion Adaptive Cavitation Feature Extraction for Hydraulic Turbine Cavitation Detection by Yi Wang, Feng Li, Mengge Lv, Tianzhen Wang, Xiaohang Wang

“…A multi-index fusion adaptive cavitation feature extraction and cavitation detection method is proposed to solve the above problems. The number of decomposition layers in the multi-index fusion variational mode decomposition (VMD) algorithm is adaptively determined by fusing multiple indicators related to cavitation characteristics, thus retaining more cavitation information and improving the quality of cavitation feature extraction. …”
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Limited Data Availability in Building Energy Consumption Prediction: A Low-Rank Transfer Learning with Attention-Enhanced Temporal Convolution Network by Bo Wang, Qiming Fu, You Lu, Ke Liu

“…However, while data-driven methods have emerged as a crucial method to solving this complex problem, the limited availability of data presents a significant challenge to model training. …”
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Tensor-Based Cybersecurity Analysis of Smart Grids Using IT/OT Convergence by Danial Jafarigiv, Keyhan Sheshyekani, Marthe Kassouf

“…The effectiveness of the low-rank modeling using both decompositions is confirmed by demonstrating relatively low reconstruction error. …”
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Integrating 3D printing, simulations and surrogate modelling: A comprehensive study on additive manufacturing focusing on a metal twin-cantilever benchmark by C. Mallor, S. Lani, V. Zambrano, H. Ghasemi-Tabasi, S. Calvo, A. Burn

“…The reduced order method for creating the surrogate model is based on tensor decomposition and designed for easy integration into a digital twin, while preserving the underlying physics by retaining the effects of input variables on the final output. …”
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Resilience-oriented Transmission Expansion Planning with Optimal Transmission Switching Under Typhoon Weather by Yang Yuan, Heng Zhang, Haozhong Cheng, Zheng Wang

“…A nested decomposition algorithm based on benders decomposition is developed to solve the model. …”
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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…The case study demonstrated that the combined prediction model effectively addressed the environmental factors affecting reservoir water levels, leveraged the strength of each predictive method, compensated for their limitations, and clarified the impacts of environmental factors on reservoir water levels.…”
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Multi-View Robust Tensor-Based Subspace Clustering by Esraa M. Al-Sharoa, Mohammad A. Al-Wardat

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System Optimization Scheduling Considering the Full Process of Electrolytic Aluminum Production and the Integration of Thermal Power and Energy Storage by Yulong Yang, Han Yan, Jiaqi Wang, Weiyang Liu, Zhongwen Yan

“…Firstly, to explore the differentiated response capabilities of various devices such as high-energy-consuming electrolytic aluminum units, thermal power units, and energy storage devices to effectively address uncertain variables in the power system, a Variational Mode Decomposition method is introduced to construct differentiated response methods for its low-frequency, medium-frequency, and high-frequency components. …”
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Multivariate Analyses with Two-Step Dimension Reduction for an Association Study Between ¹¹C-Pittsburgh Compound B and Magnetic Resonance Imaging in Alzheimer’s Disease... by Atsushi Kawaguchi, Fumio Yamashita

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Optimizing Chlorophyll-a Concentration Inversion in Coastal Waters Using SVD and Deep Learning Approach by Lili Zhan, Yongxin Xu, Jinshan Zhu, Zhangshuo Liu

“…Other machine learning methods, such as random forest (RF) and the support vector machine (SVM) are also used to establish the inversion models for the comparison. …”
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Wind speed forecasting approach using conformal prediction and feature importance selection by Cesar Vinicius Zuege, Stefano Frizzo Stefenon, Cristina Keiko Yamaguchi, Viviana Cocco Mariani, Gabriel Villarrubia Gonzalez, Leandro dos Santos Coelho

“…Furthermore, a Bayesian Optimization with Tree-structured Parzen Estimators (BO-TPE) will be used to tune the hyperparameters of the models. The results showed that using Variational Mode Decomposition (VMD) allied with Singular Spectrum Analysis (SSA) to feed into a conformal prediction model improved the performance of the model. …”
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Urban-Rural Disparities in Depressive Symptoms Among Employed Individual: Education Plays an Important Role by Xie C, Zhao Z, Gao L, Yuan L, Liu L

“…The Fairlie decomposition method was employed to investigate the impact of education level and other influencing factors on the urban-rural differences in the occurrence of depressive symptoms.Results: The proportion of depressive symptoms among employed persons in China was 14.51%. …”
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KAS: A Kernel Alignment-Based Sampling Probability Approach for Medical Data Valuation by Mingming Jiang, Qinghe Liu, Hongli Xu, Wenting Liao, Rilige Wu, Longji Li, Yawei Zhao, Kunlun He

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