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Jie Wang, Jie Yang, Jiafan He and Dongliang Peng
Semi-supervised learning has been proven to be effective in utilizing unlabeled samples to mitigate the problem of limited labeled data. Traditional semi-supervised learning methods generate pseudo-labels for unlabeled samples and train the classifier us...
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Yalin Dai, Zhouwei Fan, Jian Xu, You He and Xiongqing Yu
A special feature of airbreathing hypersonic aircraft is the complex coupling between aerodynamic and propulsive performances. This study presents a rapid analysis methodology for the integration of these two critical aspects in the conceptual design of ...
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Anqing Wang, Longwei Li, Haoliang Wang, Bing Han and Zhouhua Peng
In this paper, a swarm trajectory-planning method is proposed for multiple autonomous surface vehicles (ASVs) in an unknown and obstacle-rich environment. Specifically, based on the point cloud information of the surrounding environment obtained from loc...
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Wenhao Sun, Yidong Zou, Yunhe Wang, Boyi Xiao, Haichuan Zhang and Zhihuai Xiao
In the practical production environment, the complexity and variability of hydroelectric units often result in a need for more fault data, leading to inadequate accuracy in fault identification for data-driven intelligent diagnostic models. To address th...
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Vinh Pham, Maxim Tyan, Tuan Anh Nguyen and Jae-Woo Lee
Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity...
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