Data-driven xgboost model for maximum stress prediction of additive manufactured lattice structures

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SUMMARY

    Metal lattice structures produced by additive manufacturing (AM) have attracted extensive attention owing to their advantages such as light weight, complex structure, and integrated structure function. Jin et_al summarised the application of machine_learning in AM in detail. The maximum stress can be a good reflection of the load-bearing capacity of the structure and can sim- plify the complexity of the prediction model when combined with machine_learning. The aforementioned studies are characterised by a novel and promising research field, namely, a hybrid_approach between meta-heuristics and machine_learning. This new field of research successfully combines . . .

     

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