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Bowen Xing, Xiao Wang and Zhenchong Liu
The path planning strategy of deep-sea mining vehicles is an important factor affecting the efficiency of deep-sea mining missions. However, the current traditional path planning algorithms suffer from hose entanglement problems and small coverage in the...
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Hy Nguyen, Srikanth Thudumu, Hung Du, Kon Mouzakis and Rajesh Vasa
Several approaches have applied Deep Reinforcement Learning (DRL) to Unmanned Aerial Vehicles (UAVs) to do autonomous object tracking. These methods, however, are resource intensive and require prior knowledge of the environment, making them difficult to...
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Tongyang Xu, Yuan Liu, Zhaotai Ma, Yiqiang Huang and Peng Liu
As a new distributed machine learning (ML) approach, federated learning (FL) shows great potential to preserve data privacy by enabling distributed data owners to collaboratively build a global model without sharing their raw data. However, the heterogen...
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Alamir Labib Awad, Saleh Mesbah Elkaffas and Mohammed Waleed Fakhr
Stock value prediction and trading, a captivating and complex research domain, continues to draw heightened attention. Ensuring profitable returns in stock market investments demands precise and timely decision-making. The evolution of technology has int...
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Bowen Xing, Xiao Wang, Liu Yang, Zhenchong Liu and Qingyun Wu
A deep reinforcement learning method to achieve complete coverage path planning for an unmanned surface vehicle (USV) is proposed. This paper firstly models the USV and the workspace required for complete coverage. Then, for the full-coverage path planni...
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Junkai Yi and Xiaoyan Liu
Penetration testing is an important method to evaluate the security degree of a network system. The importance of penetration testing attack path planning lies in its ability to simulate attacker behavior, identify vulnerabilities, reduce potential losse...
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Wenhao Ma and Hongzhen Xu
Cloud computing has experienced rapid growth in recent years and has become a critical computing paradigm. Combining multiple cloud services to satisfy complex user requirements has become a research hotspot in cloud computing. Service composition in mul...
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Zeyang Wang, Jun Huang and Mingxu Yi
Unmanned aerial helicopters (UAHs) have been widely used recently for reconnaissance operations and other risky missions. Meanwhile, the threats to UAHs have been becoming more and more serious, mainly from radar and flights. It is essential for a UAH to...
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Shao Xuan Seah and Sutthiphong Srigrarom
This paper explores the use of deep reinforcement learning in solving the multi-agent aircraft traffic planning (individual paths) and collision avoidance problem for a multiple UAS, such as that for a cargo drone network. Specifically, the Deep Q-Networ...
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Pir Dino Soomro, Xianping Fu, Muhammad Aslam, Dani Elias Mfungo and Arsalan Ali
An imperative application of artificial intelligence (AI) techniques is visual object detection, and the methods of visual object detection available currently need highly equipped datasets preserved in a centralized unit. This usually results in high tr...
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