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Lin Guo, Anand Balu Nellippallil, Warren F. Smith, Janet K. Allen and Farrokh Mistree
When dealing with engineering design problems, designers often encounter nonlinear and nonconvex features, multiple objectives, coupled decision making, and various levels of fidelity of sub-systems. To realize the design with limited computational resou...
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Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
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Yunfei Yang, Zhicheng Zhang, Jiapeng Zhao, Bin Zhang, Lei Zhang, Qi Hu and Jianglong Sun
Resistance serves as a critical performance metric for ships. Swift and accurate resistance prediction can enhance ship design efficiency. Currently, methods for determining ship resistance encompass model tests, estimation techniques, and computational ...
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Radoslaw Piotr Katarzyniak, Grzegorz Popek and Marcin Zurawski
This article presents a model of an architecture of an artificial cognitive agent that performs the function of generating autoepistemic membership statements used to communicate beliefs about the belonging of an observed external object to a category wi...
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Changhao Wu, Siyang He, Zengshan Yin and Chongbin Guo
Large-scale low Earth orbit (LEO) remote satellite constellations have become a brand new, massive source of space data. Federated learning (FL) is considered a promising distributed machine learning technology that can communicate optimally using these ...
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