LPBF processing parameters used and their respective volumetric energy density.

<p>LPBF processing parameters used and their respective volumetric energy density.</p>

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Bibliographic Details
Main Author:	Vijaykumar S. Jatti (19251057) (author)
Other Authors:	A. Saiyathibrahim (21464715) (author), Arvind Yadav (7196642) (author), Murali Krishnan R. (21464718) (author), B. Jayaprakash (21464721) (author), Sumit Kaushal (21464724) (author), Vinaykumar S. Jatti (19251066) (author), Ashwini V. Jatti (21464727) (author), Savita V. Jatti (21464730) (author), Abhinav Kumar (308176) (author), Soumaya Gouadria (12988442) (author), Ebenezer Bonyah (4491601) (author)
Published:	2025
Subjects:	Molecular Biology Physiology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified mean absolute error machine learning algorithms lr model performs forecasted using trained several performance indicators better predictive performance predict tensile properties lower error values div >< p different tensile characteristics 2 </ sup various mlr models evaluated mlr models rmse ), r predicting tensile properties heat treated samples tensile properties tensile characteristics treated samples tensile features rfr ), mse ), three models uts value scatter plots mae ). linear regression high precision heat treated dt ). decision tree alsi10mg alloys alsi10mg alloy additive manufacturing
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