Hyper parameter settings for ML Algorithms.

<div><p>3D printing has brought significant changes to manufacturing sectors, making it possible to produce intricate, multi-layered designs with greater ease. This study focuses on optimizing the compressive strength (CS) of functionally graded multi-material (PLA/Almond Shell Reinforce...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	R. S. Jayaram (22139155) (author)
مؤلفون آخرون:	P. Saravanamuthukumar (22139158) (author), Ahmad Baharuddin Abdullah (22139161) (author), Ramalingam Krishnamoorthy (22139164) (author), Sandip Kunar (22139167) (author), Xu Yong (12675832) (author), S. Prabhakar (20051421) (author)
منشور في:	2025
الموضوعات:	Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified traditional taguchi method shap analysis indicated namely print speed improved mechanical performance brought significant changes 216 ° c lowest error metrics functionally graded multi div >< p 2 </ sup lower error low error study focuses produce intricate printing temperature polynomial regression performed best manufacturing sectors layered designs influential parameter greater ease fgms suitable fff process experimentally validated compressive strength 8 mpa 74 mpa 6 ). 44 %. 3d printing 36 mpa 19 mm
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Hyper parameter settings for ML Algorithms.

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