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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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Hamad Almaghrabi, Ben Soh and Alice Li
Effective and efficient use of information and communication technology (ICT) systems in the administration of educational organisations is crucial to optimise their performance. Earlier research on the identification and analysis of ICT users? satisfact...
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Qiankun Wang, Ke Zhu, Peiwen Guo, Jiaji Zhang and Zhihua Xiong
Faced with the challenges of global climate change, zero-carbon buildings (ZCB) serve as a crucial means to achieve carbon peak and carbon neutrality goals, particularly in the development of tropical island regions. This study aims to establish a ZCB te...
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Cai Wu, Yanwen Wang, Jiong Wang, Menno-Jan Kraak and Mingshu Wang
This study introduces a machine learning-based framework for mapping street patterns in urban morphology, offering an objective, scalable approach that transcends traditional methodologies. Focusing on six diverse cities, the research employed supervised...
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Jaehan Jeon and Gerasimos Theotokatos
Digital twins (DTs) are gradually employed in the maritime industry to represent the physical systems and generate datasets, among others. However, the trustworthiness of both the digital twins and datasets must be assured. This study aims at developing ...
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Chao-Chung Peng and Yi-Ho Chen
Digital twins can reflect the dynamical behavior of the identified system, enabling self-diagnosis and prediction in the digital world to optimize the intelligent manufacturing process. One of the key benefits of digital twins is the ability to provide r...
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Higuatzi Moreno and Alexander Schaum
Batteries are complex systems involving spatially distributed microscopic mechanisms on different time scales whose adequate interplay is essential to ensure a desired functioning. Describing these phenomena yields nonlinearly coupled partial differentia...
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Juseong Lee, Mihaela Mitici, Henk A. P. Blom, Pierre Bieber and Floris Freeman
The increasing use of on-board sensor monitoring and data-driven algorithms has stimulated the recent shift to data-driven predictive maintenance for aircraft. This paper discusses emerging challenges for data-driven predictive aircraft maintenance. We i...
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Tayyab Manzoor, Hailong Pei, Zhongqi Sun and Zihuan Cheng
This paper proposes a model predictive control (MPC) approach for ducted fan aerial robots using physics-informed machine learning (ML), where the task is to fully exploit the capabilities of the predictive control design with an accurate dynamic model b...
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Wenbo He, Xiaoqiang Zhang, Zhenyu Feng, Qiqi Leng, Bufeng Xu and Xinmin Li
Dynamic load identification plays an important role in the field of fault diagnosis and structural modification design for aircraft. In conventional dynamic load identification approaches, accurate structural modeling is usually needed, which is difficul...
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