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Titlebook: Advances and Trends in Artificial Intelligence. Theory and Applications; 36th International C Hamido Fujita,Yinglin Wang,Ali Moonis Confere

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發(fā)表于 2025-3-21 18:02:35 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advances and Trends in Artificial Intelligence. Theory and Applications
期刊簡稱36th International C
影響因子2023Hamido Fujita,Yinglin Wang,Ali Moonis
視頻videohttp://file.papertrans.cn/147/146583/146583.mp4
學科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advances and Trends in Artificial Intelligence. Theory and Applications; 36th International C Hamido Fujita,Yinglin Wang,Ali Moonis Confere
影響因子.This double volume LNAI 13925-13926 constitutes the thoroughly refereed proceedings of the 36th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2023, held in Shanghai, China, in July 2023...The 50 full papers and 20 short papers presented were carefully reviewed and selected from 129 submissions. The IEA/AIE 2023 conference on applications of applied intelligent systems to solve real-life problems in all areas including business and finance, science, engineering, industry, cyberspace, bioinformatics, automation, robotics, medicine and biomedicine, and human-machine interactions..
Pindex Conference proceedings 2023
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https://doi.org/10.1007/978-3-662-30754-0oBERTa model. Using this, we were able to achieve a 6% overall improvement in the f1 score in EverestNER Dataset. In terms of the fields, we have achieved an increase of up to 22% in the f1 score for the Event entity which has the lowest support.
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https://doi.org/10.1007/978-1-349-04790-1ity and customizability. Furthermore, we provide empirical evidence that our model exhibits comparable performance regarding learning speed and accuracy to a similar model based on multi-layer perceptrons.
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https://doi.org/10.1007/978-3-642-53172-9on regarding the source of observations. Furthermore, we suggest implementing properties using ordinary programming languages from which we can obtain a formal model directly. Finally, we explain the process of integrating diagnosis into monitoring and show its value using a case study from the automotive domain.
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