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    MSVMD-Informer: A Multi-Variate Multi-Scale Method to Wind Power Prediction by Zhijian Liu, Jikai Chen, Hang Dong, Zizhuo Wang

    Published 2025-03-01
    “…Wind power prediction plays a crucial role in enhancing power grid stability and wind energy utilization efficiency. Existing prediction methods demonstrate insufficient integration of multi-variate features, such as wind speed, temperature, and humidity, along with inadequate extraction of correlations between variables. …”
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  3. 43

    UNDERSTANDING REGIONAL INTEGRATION VARIATION AND THE ADOPTION OF NEW TECHNOLOGY: EU AND ASEAN LEGAL FRAMEWORK ON ELECTROMOBILITY IN COMPARATIVE PERSPECTIVES by Asrul Ibrahim NUR

    Published 2023-06-01
    “…Furthermore, this study will discuss the variation and comparative influence of EU and ASEAN regional integration on adopting new technologies, namely EVs, in the context of climate change adaptation. …”
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  4. 44

    A Numerical Method Based on the Parametric Variational Principle for Simulating the Dynamic Behavior of the Pantograph-Catenary System by Dongdong He, Qiang Gao, Wanxie Zhong

    Published 2018-01-01
    “…Based on the finite element method (FEM), the parametric variational principle (PVP) is combined with a numerical time-domain integral method to simulate the dynamic behavior of the pantograph-catenary system. …”
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  5. 45

    MGV-seq: a sensitive and culture-independent method for detecting microbial genetic variation by Lun Li, Weiyu Kong, Jing Sun, Yongzhong Jiang, Tiantian Li, Zhihui Xia, Junfei Zhou, Zhiwei Fang, Lihong Chen, Shun Feng, Huiyin Song, Huafeng Xiao, Baolong Zhang, Bin Fang, Hai Peng, Hai Peng, Lifen Gao, Lifen Gao

    Published 2025-06-01
    “…To address these challenges, we developed MGV-Seq, an innovative culture-independent approach that integrates multiplex PCR, high-throughput sequencing, and bioinformatics to analyze multiple dispersed nucleotide polymorphism (MNP) markers, enabling high-resolution strain differentiation.MethodsUsing Xanthomonas oryzae as a model organism, we designed 213 MNP markers derived from 458 genome assemblies. …”
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  6. 46

    Variational Iteration Method for Nonlinear Singular Two-Point Boundary Value Problems Arising in Human Physiology by Marwan Abukhaled

    Published 2013-01-01
    “…The variational iteration method is applied to solve a class of nonlinear singular boundary value problems that arise in physiology. …”
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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

    Published 2025-01-01
    “…To address the curtailment phenomenon caused by the high penetration of renewable energy in the system, an optimization scheduling strategy is proposed, considering the full process of electrolytic aluminum production and the integration of thermal power and energy storage. 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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    Crude Oil Futures Price Forecasting Based on Variational and Empirical Mode Decompositions and Transformer Model by Linya Huang, Xite Yang, Yongzeng Lai, Ankang Zou, Jilin Zhang

    Published 2024-12-01
    “…This model integrates a second decomposition and Transformer model-based machine learning method. …”
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  13. 53

    Boundary integral equation methods for Lipschitz domains in linear elasticity by Le Louër, Frédérique

    Published 2024-05-01
    “…A review of stable boundary integral equation methods for solving the Navier equation with either Dirichlet or Neumann boundary conditions in the exterior of a Lipschitz domain is presented. …”
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  14. 54

    Method based on contrastive incremental learning for fine-grained malicious traffic classification by Yifeng WANG, Yuanbo GUO, Qingli CHEN, Chen FANG, Renhao LIN, Yongliang ZHOU, Jiali MA

    Published 2023-03-01
    “…In order to protect against continuously emerging unknown threats, a new method based on contrastive incremental learning for fine-grained malicious traffic classification was proposed.The proposed method was based on variational auto-encoder (VAE) and extreme value theory (EVT), and the high accuracy could be achieved in known, few-shot and unknown malicious classes and new classes were also identified without using a large number of old task samples, which met the demand of storage and time cost in incremental learning scenarios.Specifically, the contrastive learning was integrated into the encoder of VAE, and the A-Softmax was used for known and few-shot malicious traffic classification, EVT and the decoder of VAE were used for unknown malicious traffic recognition, all classes could be recognized without a lot of old samples when learning new tasks by using VAE reconstruction and knowledge distillation methods.Experimental results indicate that the proposed method is efficient in known, few-shot and unknown malicious classes, and has greatly reduced the forgetting speed of old knowledge in incremental learning scenarios.…”
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    Evaluation and prediction of coal seam mining mode: Coefficient of Variation-TOPSIS and CNN-NGO methods by Haixiong Li, Fei Wang

    Published 2025-01-01
    “…This study explores and validates an integrated evaluation system that enhances the accuracy of predicting coal seam mining mode by comparing traditional evaluation methods with machine-learning techniques. …”
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    SiRCle (Signature Regulatory Clustering) model integration reveals mechanisms of phenotype regulation in renal cancer by Ariane Mora, Christina Schmidt, Brad Balderson, Christian Frezza, Mikael Bodén

    Published 2024-12-01
    “…Methods Here, we present SiRCle (Signature Regulatory Clustering), a method to integrate DNA methylation, RNA-seq and proteomics data at the gene level by following central dogma of biology, i.e. genetic information proceeds from DNA, to RNA, to protein. …”
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