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Biplov Bhandari, Kel Markert, Vikalp Mishra, Amanda Markert and Robert Griffin
Flooding is a recurring natural disaster worldwide; developing countries are particularly affected due to poor mitigation and management strategies. Often discharge is used to inform the flood forecast. The discharge is usually inferred from the water le...
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Jeongeun Won, Jiyu Seo, Jeonghoon Lee, Jeonghyeon Choi, Yoonkyung Park, Okjeong Lee and Sangdan Kim
River runoff predictions in ungauged basins are one of the major challenges in hydrology. In the past, the approach using a physical-based conceptual model was the main approach, but recently, a solution using a data-driven model has been evaluated as mo...
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Die Zhang, Yong Ge, Xilin Wu, Haiyan Liu, Wenbin Zhang and Shengjie Lai
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accurac...
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Roberto Boccagna, Maurizio Bottini, Massimo Petracca, Alessia Amelio and Guido Camata
In the last few decades, structural health monitoring has gained relevance in the context of civil engineering, and much effort has been made to automate the process of data acquisition and analysis through the use of data-driven methods. Currently, the ...
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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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