Metal–Metal Bonding Process Research Based on Xgboost Machine Learning Algorithm

Conventionally, the optimization of bonding process parameters requires multi-parameter repetitive experiments, the processing of data, and the characterization of complex relationships between process parameters, and performance must be achieved with the help of new technologies. This work focused...

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Vydané v:	Polymers Ročník 15; číslo 20; s. 4085
Hlavní autori:	Feng, Jingpeng, Zhan, Lihua, Ma, Bolin, Zhou, Hao, Xiong, Bang, Guo, Jinzhan, Xia, Yunni, Hui, Shengmeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 14.10.2023 MDPI
Predmet:	Adhesive bonding Algorithms Analysis Curing Experimental methods Finite element method Interfacial bonding Machine learning Mathematical models Metal bonding Metal-metal bonding Methods New technology Optimization Process parameters Research methodology Shear strength Thickness China
ISSN:	2073-4360, 2073-4360
On-line prístup:	Získať plný text
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