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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Juan Ma, Qiang Yang, Mingzhi Zhang, Yao Chen, Wenyi Zhao, Chengyu Ouyang and Dongping Ming
Accurately predicting landslide deformation based on monitoring data is key to successful early warning of landslide disasters. Landslide displacement?time curves offer an intuitive reflection of the landslide motion process and deformation predictions o...
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Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio...
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Haoyu Lin, Pengkun Quan, Zhuo Liang, Dongbo Wei and Shichun Di
In the context of automatic charging for electric vehicles, collision localization for the end-effector of robots not only serves as a crucial visual complement but also provides essential foundations for subsequent response design. In this scenario, dat...
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Sabrina De Nardi, Claudio Carnevale, Sara Raccagni and Lucia Sangiorgi
Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-dr...
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Hugo Valayer, Nathalie Bartoli, Mauricio Castaño-Aguirre, Rémi Lafage, Thierry Lefebvre, Andrés F. López-Lopera and Sylvain Mouton
In aerodynamics, characterizing the aerodynamic behavior of aircraft typically requires a large number of observation data points. Real experiments can generate thousands of data points with suitable accuracy, but they are time-consuming and resource-int...
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Javensius Sembiring, Rianto Adhy Sasongko, Eduardo I. Bastian, Bayu Aji Raditya and Rayhan Ekananto Limansubroto
This paper investigates the development of a deep learning-based flight control model for a tilt-rotor unmanned aerial vehicle, focusing on altitude, speed, and roll hold systems. Training data is gathered from the X-Plane flight simulator, employing a p...
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Boqian Ji, Jun Huang, Xiaoqiang Lu, Yacong Wu and Jingjiang Liu
The wing aerodynamic shape optimization is a typical high-dimensional problem with numerous independent design variables. Researching methods to reduce the dimensionality of optimization from the perspective of aerodynamic characteristics is necessary. O...
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Zhiqiang Jiang, Yongyan Ma and Weijia Li
Accurate forecasting of ship motion is of great significance for ensuring maritime operational safety and working efficiency. A data-driven ship motion forecast method is proposed in this paper, aiming at the problems of low generalization of a single fo...
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Sajjad E. Rasheed, Duaa Al-Jeznawi, Musab Aied Qissab Al-Janabi and Luís Filipe Almeida Bernardo
The structural stability of pipe pile foundations under seismic loading stands as a critical concern, demanding an accurate assessment of the maximum settlement. Traditionally, this task has been addressed through complex numerical modeling, accounting f...
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