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  1. 41

    Short-term load forecasting based on multi-frequency sequence feature analysis and multi-point modified FEDformer by Kaiyuan Hou, Xiaotian Zhang, Junjie Yang, Jiyun Hu, Guangzhi Yao, Jiannan Zhang

    Published 2025-01-01
    “…Given the complexity and dynamic nature of short-term load sequence data, coupled with prevalent errors in traditional forecasting methods, this study introduces a novel approach for short-term load forecasting. …”
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    SFPFMformer: Short-Term Power Load Forecasting for Proxy Electricity Purchase Based on Feature Optimization and Multiscale Decomposition by Chengfei Qi, Yanli Feng, Junling Wan, Xinying Mao, Peisen Yuan

    Published 2025-05-01
    “…Finally, we utilize a depthwise separable convolution block to extract features from power load data, which efficiently captures the pattern of change in load. …”
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  4. 44

    Monopulse Feature Extraction and Fault Diagnosis Method of Rolling Bearing under Low-Speed and Heavy-Load Conditions by Chang Liu, Gang Cheng, Xihui Chen, Yong Li

    Published 2021-01-01
    “…According to the rolling bearing local fault vibration mechanism, a monopulse feature extraction and fault diagnosis method of rolling bearing under low-speed and heavy-load conditions based on phase scan and CNN is proposed. …”
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    Multi-Dimensional AE Signal Features in Eccentrically Loaded Concrete Structures: A Machine Learning Classification for Damage Progression by Shilong Ding, Alipujiang Jierula, Abudusaimaiti Kali, Tong Han, Tae-Min Oh

    Published 2025-06-01
    “…This study employed K-means clustering algorithm and Gaussian mixture models (GMMs) to analyze AE signal features from reinforced concrete (RC) columns undergoing failure under the eccentric compression loading of different eccentricity. …”
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    An electrical load forecasting model based on a novel closed loop neural networks and interaction gain feature selection by Gholamreza Memarzadeh, Faezeh Amirteimoury, Hossein Noori, Farshid Keynia

    Published 2025-09-01
    “…Accurate short-term load forecasting, particularly for normal and peak load values, plays a critical role in ensuring the reliable and efficient operation of modern power systems. …”
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    Article
  9. 49

    A multi-modal feature combination mechanism for identification of harmonic load in distribution networks based on artificial intelligence models by Renzeng Yang, Shuang Peng, Gang Yao

    Published 2025-05-01
    “…The most suitable intrinsic mode sequences are selected as input features for sequential neural networks training. Finally, a multi-modal feature tensor combination mechanism that integrates reshaped vector layers into the sequential neural networks architecture is introduced, enabling adaptive extraction of spatial–temporal characteristics and significantly improving the accuracy of harmonic load identification without prior knowledge of their spectral features.…”
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  10. 50

    Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks by Xiaoguang Wei, Shibin Gao, Tao Huang, Tao Wang, Wenli Fan

    Published 2019-01-01
    “…This paper proposes a new framework to analyze two vulnerability features, impactability and susceptibility, in electrical networks under deliberate attacks based on complex network theory: these two features are overlooked but vital in vulnerability analyses. …”
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    A Multi-stage Scenario Tree Generation Method for Wind-Solar Load Based on Complex Feature Extraction and Sinkhorn Distance by Rui WANG, Zhixin FU, Jian WANG, Haoming LIU

    Published 2024-12-01
    “…Firstly, to enhance the clustering efficiency of wind-solar load scenarios, a method based on stacked sparse autoencoders for feature extraction of wind-solar load scenarios was introduced. …”
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  15. 55

    New State Identification Method for Rotating Machinery under Variable Load Conditions Based on Hybrid Entropy Features and Joint Distribution Adaptation by Xiaoming Xue, Nan Zhang, Suqun Cao, Wei Jiang, Jianzhong Zhou, Liyan Liu

    Published 2020-01-01
    “…Finally, five cases with the training and testing set under variable load conditions were used to demonstrate the performance of the proposed method, and comparisons with some other diagnosis models combined with the same features and other dimensionality reduction methods were also discussed. …”
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    Article
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