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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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Li Li and Kyung Soo Jun
River flood routing computes changes in the shape of a flood wave over time as it travels downstream along a river. Conventional flood routing models, especially hydrodynamic models, require a high quality and quantity of input data, such as measured hyd...
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Shitu Chen, Ling Feng, Xuteng Bao, Zhe Jiang, Bowen Xing and Jingxiang Xu
Path planning is crucial for unmanned surface vehicles (USVs) to navigate and avoid obstacles efficiently. This study evaluates and contrasts various USV path-planning algorithms, focusing on their effectiveness in dynamic obstacle avoidance, resistance ...
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Jing Luo, Yuhang Zhang, Jiayuan Zhuang and Yumin Su
The development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm tha...
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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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