Comparison C<sub>p</sub> for training and test sets across ML models.
<p>Comparison C<sub>p</sub> for training and test sets across ML models.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
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| _version_ | 1852017211200241664 |
|---|---|
| author | R. S. Jayaram (22139155) |
| author2 | P. Saravanamuthukumar (22139158) Ahmad Baharuddin Abdullah (22139161) Ramalingam Krishnamoorthy (22139164) Sandip Kunar (22139167) Xu Yong (12675832) S. Prabhakar (20051421) |
| author2_role | author author author author author author |
| author_facet | R. S. Jayaram (22139155) P. Saravanamuthukumar (22139158) Ahmad Baharuddin Abdullah (22139161) Ramalingam Krishnamoorthy (22139164) Sandip Kunar (22139167) Xu Yong (12675832) S. Prabhakar (20051421) |
| author_role | author |
| dc.creator.none.fl_str_mv | R. S. Jayaram (22139155) P. Saravanamuthukumar (22139158) Ahmad Baharuddin Abdullah (22139161) Ramalingam Krishnamoorthy (22139164) Sandip Kunar (22139167) Xu Yong (12675832) S. Prabhakar (20051421) |
| dc.date.none.fl_str_mv | 2025-08-28T17:35:22Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0330625.g010 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Comparison_C_sub_p_sub_for_training_and_test_sets_across_ML_models_/30004411 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | 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 |
| dc.title.none.fl_str_mv | Comparison C<sub>p</sub> for training and test sets across ML models. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Comparison C<sub>p</sub> for training and test sets across ML models.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_69b2f376f79d3208bfcaaed00cdbdc0e |
| identifier_str_mv | 10.1371/journal.pone.0330625.g010 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30004411 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparison C<sub>p</sub> for training and test sets across ML models.R. S. Jayaram (22139155)P. Saravanamuthukumar (22139158)Ahmad Baharuddin Abdullah (22139161)Ramalingam Krishnamoorthy (22139164)Sandip Kunar (22139167)Xu Yong (12675832)S. Prabhakar (20051421)Science PolicySpace ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedtraditional taguchi methodshap analysis indicatednamely print speedimproved mechanical performancebrought significant changes216 ° clowest error metricsfunctionally graded multidiv >< p2 </ suplower errorlow errorstudy focusesproduce intricateprinting temperaturepolynomial regressionperformed bestmanufacturing sectorslayered designsinfluential parametergreater easefgms suitablefff processexperimentally validatedcompressive strength8 mpa74 mpa6 ).44 %.3d printing36 mpa19 mm<p>Comparison C<sub>p</sub> for training and test sets across ML models.</p>2025-08-28T17:35:22ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0330625.g010https://figshare.com/articles/figure/Comparison_C_sub_p_sub_for_training_and_test_sets_across_ML_models_/30004411CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/300044112025-08-28T17:35:22Z |
| spellingShingle | Comparison C<sub>p</sub> for training and test sets across ML models. R. S. Jayaram (22139155) 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 |
| status_str | publishedVersion |
| title | Comparison C<sub>p</sub> for training and test sets across ML models. |
| title_full | Comparison C<sub>p</sub> for training and test sets across ML models. |
| title_fullStr | Comparison C<sub>p</sub> for training and test sets across ML models. |
| title_full_unstemmed | Comparison C<sub>p</sub> for training and test sets across ML models. |
| title_short | Comparison C<sub>p</sub> for training and test sets across ML models. |
| title_sort | Comparison C<sub>p</sub> for training and test sets across ML models. |
| topic | 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 |