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Xinyue Zhao, Fangxu Gui, Heng Chen, Lanxin Fan and Peiyuan Pan
Transformers, as the hub equipment of the power system, are highly valued by engineering and scientific researchers in production practice and scientific research. The goal of transformer research is to ensure the safe operation of transformers while con...
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Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio...
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Vicente León-Martínez, Elisa Peñalvo-López, Juan Ángel Sáiz-Jiménez and Amparo León-Vinet
Short-circuit resistances are transformer parameters that characterize the electrical load losses and correct operation of these machines. However, the traditional concept of short-circuit resistance, independent of the harmonic frequencies, has been sup...
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A. M. Sakura R. H. Attanayake and R. M. Chandima Ratnayake
Digitalization of the failure-probability modeling of crucial components in power-distribution systems is important for improving risk and reliability analysis for system-maintenance and asset-management practices. This paper aims to implement a Python p...
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Lu Sun, Shuguo Gao, Tianran Li, Jiaxin Yao, Ping Wang and Jianhao Zhu
The instability of the winding-cushion structure is one of the primary causes of transformer failures. Insulation cushion compression and offset are the predominant forms leading to structural instability. Therefore, this paper, using the SFSZ7-31500/110...
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Leila Ben Letaifa and Jean-Luc Rouas
Transformer models are being increasingly used in end-to-end speech recognition systems for their performance. However, their substantial size poses challenges for deploying them in real-world applications. These models heavily rely on attention and feed...
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Guobiao Yao, Jin Zhang, Jianya Gong and Fengxiang Jin
To promote the development of deep learning for feature matching, image registration, and three-dimensional reconstruction, we propose a method of constructing a deep learning benchmark dataset for affine-invariant feature matching. Existing images often...
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Minghui Sha, Dewu Wang, Fei Meng, Wenyan Wang and Yu Han
With the increasing complexity of radar jamming threats, accurate and automatic jamming recognition is essential but remains challenging. Conventional algorithms often suffer from sharply decreased recognition accuracy under low jamming-to-noise ratios (...
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Wei Li, Xi Zhan, Xin Liu, Lei Zhang, Yu Pan and Zhisong Pan
Traffic prediction plays a significant part in creating intelligent cities such as traffic management, urban computing, and public safety. Nevertheless, the complex spatio-temporal linkages and dynamically shifting patterns make it somewhat challenging. ...
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Guangming Ling, Xiaofeng Mu, Chao Wang and Aiping Xu
Address parsing is a crucial task in natural language processing, particularly for Chinese addresses. The complex structure and semantic features of Chinese addresses present challenges due to their inherent ambiguity. Additionally, different task scenar...
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