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Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li and Fengjun Hu
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
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Xiaori Gao, Lidong Wang, Zeyu Wu and Xiaodong Liu
The steady turning motion of merchant ships is modeled according to industry specifications. However, challenges arise when motorboats are modeled. This study proposes a novel data-driven multi-block fuzzy cognitive map (FCM) model trained based on sea t...
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Okan Bulut, Guher Gorgun, Tarid Wongvorachan and Bin Tan
Rapid guessing is an aberrant response behavior that commonly occurs in low-stakes assessments with little to no formal consequences for students. Recently, the availability of response time (RT) information in computer-based assessments has motivated re...
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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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Dezhi Cao, Yue Zhao and Licheng Wu
The construction of pronunciation dictionaries relies on high-quality and extensive training data in data-driven way. However, the manual annotation of corpus for this purpose is both costly and time consuming, especially for low-resource languages that ...
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