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This paper proposes a novel approach, utilizing deep learning trained with diverse data from existing energy management systems, to assess its adaptability to ...
An attention-based deep learning model considering data contamination for energy management system application of hybrid vehicle · Wei Huang · Yujun Zhang · Duode ...
An attention-based deep learning model considering data ...
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An attention-based deep learning model considering data contamination for energy management system application of hybrid vehicle · Wei Huang, Yujun Zhang, +3 ...
Abstract. Hybrid vehicles are pivotal in transitioning to sustainable transportation, but effective energy management is challenged by data contamination.
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Jul 3, 2023 · An attention-based deep learning model considering data contamination for energy management system application of hybrid vehicle. Wei Huang ...
An attention-based deep learning model considering data contamination for energy management system application of hybrid vehicle. Article. Aug 2024; COMPUT ...
An attention-based deep learning model considering data contamination for energy management system application of hybrid vehicle. Article. Aug 2024; COMPUT ...
An attention-based deep learning model considering data contamination for energy management system application of hybrid vehicle. Wei Huang, Yujun Zhang ...
An attention-based deep learning model considering data contamination for energy management system application of hybrid vehicle. Wei HuangYujun ZhangDuode ...
Jun 17, 2024 · This paper proposes a machine learning approach, leveraging Gaussian Process (GP) and Krill Herd Algorithm (KHA), for energy management in renewable microgrids.