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Haoyu Lin, Pengkun Quan, Zhuo Liang, Dongbo Wei and Shichun Di
With the rise of electric vehicles, autonomous driving, and valet parking technologies, considerable research has been dedicated to automatic charging solutions. While the current focus lies on charging robot design and the visual positioning of charging...
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Mirko Dinulovic, Aleksandar Benign and Bo?ko Ra?uo
In the present work, the potential application of machine learning techniques in the flutter prediction of composite materials missile fins is investigated. The flutter velocity data set required for different fin aerodynamic geometries and materials is ...
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Weihan Huang, Ke Gao and Yu Feng
Predicting earthquakes through reasonable methods can significantly reduce the damage caused by secondary disasters such as tsunamis. Recently, machine learning (ML) approaches have been employed to predict laboratory earthquakes using stick-slip dynamic...
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Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
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Zijia Zheng, Yizhu Jiang, Qiutong Zhang, Yanling Zhong and Lizheng Wang
The timely monitoring of urban water bodies using unmanned aerial vehicle (UAV)-mounted remote sensing technology is crucial for urban water resource protection and management. Addressing the limitations of the use of satellite data in inferring the wate...
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Vahid Safavi, Arash Mohammadi Vaniar, Najmeh Bazmohammadi, Juan C. Vasquez and Josep M. Guerrero
Predicting the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is crucial to preventing system failures and enhancing operational performance. Knowing the RUL of a battery enables one to perform preventative maintenance or replace the batte...
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Zhe Zheng, Bo Zou, Wenbin Wei and Wen Tian
The ability to accurately predict flight time of arrival in real time during a flight is critical to the efficiency and reliability of aviation system operations. This paper proposes a data-light and trajectory-based machine learning approach for the onl...
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Choong Hee Cho, Yang Woo Yu and Hyeon Gyu Kim
Student dropout is a serious issue in that it not only affects the individual students who drop out but also has negative impacts on the former university, family, and society together. To resolve this, various attempts have been made to predict student ...
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Tala Talaei Khoei and Naima Kaabouch
Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and detect these a...
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Xianlei Fu, Maozhi Wu, Sasthikapreeya Ponnarasu and Limao Zhang
This research introduces a hybrid deep learning approach to perform real-time forecasting of passenger traffic flow for the metro railway system (MRS). By integrating long short-term memory (LSTM) and the graph convolutional network (GCN), a hybrid deep ...
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