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Sijie Liu, Nan Zhou, Chenchen Song, Geng Chen and Yafeng Wu
This research introduces the Enhanced Scale-Aware efficient Transformer (ESAE-Transformer), a novel and advanced model dedicated to predicting Exhaust Gas Temperature (EGT). The ESAE-Transformer merges the Multi-Head ProbSparse Attention mechanism with t...
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Chengmin Zhou, Lansong Jiang and Jake Kaner
This study aims to integrate data-driven methodologies with user perception to establish a robust design paradigm. The study consists of five steps: (1) theoretical research?a review of the subject background and applications of Kansei engineering and gr...
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Yujie Zhang, Lei Zhang, Duo Sun, Kai Jin and Yu Gu
Wind power generation is a renewable energy source, and its power output is influenced by multiple factors such as wind speed, direction, meteorological conditions, and the characteristics of wind turbines. Therefore, accurately predicting wind power is ...
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Michael Tetteh, Allan de Lima, Jack McEllin, Aidan Murphy, Douglas Mota Dias and Conor Ryan
Grammatical Evolution is a Genetic Programming variant which evolves problems in any arbitrary language that is BNF compliant. Since its inception, Grammatical Evolution has been used to solve real-world problems in different domains such as bio-informat...
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Min-Kyung Lee and Inwon Lee
In this study, deep neural network (DNN) and transfer learning (TL) techniques were employed to predict the viscous resistance and wake distribution based on the positions of flow control fins (FCFs) applied to containerships of various sizes. Both metho...
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