AMPLE
发表于 2025-3-25 05:20:44
http://reply.papertrans.cn/17/1625/162479/162479_21.png
Spinal-Tap
发表于 2025-3-25 09:38:00
http://reply.papertrans.cn/17/1625/162479/162479_22.png
Concomitant
发表于 2025-3-25 14:53:40
Urban and Regional Research Internationalings and human life. Thus, successfully estimating fly-rock distance is crucial. Many researchers attempt to develop empirical, statistical, or machine learning models to accurately predict fly-rock distance. However, for most previous research, a worrying drawback is that the amount of data related
失望未来
发表于 2025-3-25 19:39:34
Marion Reiser,Everhard Holtmannh is one of the most important and widely used materials. Different concrete types such as self-consolidating concrete (SCC), ultra-high-performance concrete (UHPC), alkali-activated concrete (AAC), and recycled aggregate concrete (RAC), each have emerged with a unique set of properties. ML methods
Compassionate
发表于 2025-3-25 23:10:31
http://reply.papertrans.cn/17/1625/162479/162479_25.png
Vital-Signs
发表于 2025-3-26 03:39:57
http://reply.papertrans.cn/17/1625/162479/162479_26.png
Robust
发表于 2025-3-26 05:03:20
Artificial Intelligence in Mechatronics and Civil Engineering978-981-19-8790-8Series ISSN 2731-4855 Series E-ISSN 2731-4863
abysmal
发表于 2025-3-26 11:56:01
http://reply.papertrans.cn/17/1625/162479/162479_28.png
pulse-pressure
发表于 2025-3-26 16:10:09
Empirical, Statistical, and Machine Learning Techniques for Predicting Surface Settlement Induced b most important findings and solutions. Among the existing techniques, machine learning seems to be the most suitable and accurate in estimating settlement induced by tunnelling. These techniques, with their behind calculations and assumptions, are able to identify the best relations between indepen
reject
发表于 2025-3-26 20:35:12
A Review on the Feasibility of Artificial Intelligence in Mechatronics,is part is categorized into five subsections: iterative learning, parametric optimization, identification, controller tuning, and control problems as stabilization. Finally, in the conclusion of the chapter, the main challenges in improvements of intelligent control methods are listed.