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Qianlong Jin, Yu Tian, Weicong Zhan, Qiming Sang, Jiancheng Yu and Xiaohui Wang
Efficiently predicting high-resolution and accurate flow fields through networked autonomous marine vehicles (AMVs) is crucial for diverse applications. Nonetheless, a research gap exists in the seamless integration of data-driven flow modeling, real-tim...
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Huihui Li, Linfeng Gou, Huacong Li and Zhidan Liu
Sensor health assessments are of great importance for accurately understanding the health of an aeroengine, supporting maintenance decisions, and ensuring flight safety. This study proposes an intelligent framework based on a physically guided neural net...
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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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Anastasios Kaltsounis, Evangelos Spiliotis and Vassilios Assimakopoulos
We present a machine learning approach for applying (multiple) temporal aggregation in time series forecasting settings. The method utilizes a classification model that can be used to either select the most appropriate temporal aggregation level for prod...
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Zhenjiang Wu, Chuiyu Lu, Qingyan Sun, Wen Lu, Xin He, Tao Qin, Lingjia Yan and Chu Wu
In recent years, the groundwater level (GWL) and its dynamic changes in the Hebei Plain have gained increasing interest. The GWL serves as a crucial indicator of the health of groundwater resources, and accurately predicting the GWL is vital to prevent i...
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