自作多情 发表于 2025-3-23 09:44:36
http://reply.papertrans.cn/15/1489/148847/148847_11.png防锈 发表于 2025-3-23 16:35:34
http://reply.papertrans.cn/15/1489/148847/148847_12.png新字 发表于 2025-3-23 21:27:13
http://reply.papertrans.cn/15/1489/148847/148847_13.pngquiet-sleep 发表于 2025-3-23 22:24:57
http://reply.papertrans.cn/15/1489/148847/148847_14.png喷出 发表于 2025-3-24 04:18:40
http://reply.papertrans.cn/15/1489/148847/148847_15.pngDistribution 发表于 2025-3-24 08:37:53
http://reply.papertrans.cn/15/1489/148847/148847_16.pngpeak-flow 发表于 2025-3-24 14:36:13
http://reply.papertrans.cn/15/1489/148847/148847_17.pngFlounder 发表于 2025-3-24 15:53:35
Yongjae Kim,Yonghoon Choi,Youngnam Hanable crack growth that requires much computational time and is vulnerable. This work developed several ML models using supervised machine learning algorithms and compared their performance. These models have shown decent precision in detecting the crack growth behavior of a pre-defined semi-ellipticleft-ventricle 发表于 2025-3-24 19:52:37
http://reply.papertrans.cn/15/1489/148847/148847_19.pngN防腐剂 发表于 2025-3-25 00:18:50
Fan Zhou,Abdulla Al Ali,Kaushik Chowdhurynnected and transmit information on a massive scale. The huge amounts of data produced, quite apart from the widespread use of the internet by these battery packs, provide new challenges for researchers and regulators. A unique deep learning model with use of internet of things (IoT) is suggested in