Hybrid Taguchi and Machine Learning Framework for Optimizing and Predicting Mechanical Properties of Polyurethane/Nanodiamond Nanocomposites

This study investigates the mechanical behavior of polyurethane (PU) nanocomposites reinforced with nanodiamonds (NDs) and proposes an integrated optimization–prediction framework that combines the Taguchi method with machi... | Find, read and cite all the research you need on Tech Science Press

Authors

Publication Details

Journal
Computer Modeling in Engineering & Sciences
Published
2025-01-01
DOI
https://doi.org/10.32604/cmes.2025.069395
Citations
1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.52
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article

Hybrid Taguchi and Machine Learning Framework for Optimizing and Predicting Mechanical Properties of Polyurethane/Nanodiamond Nanocomposites

Santosh Kumar Sahu, Markapudi Bhanu Prasad, Borhen Louhichi
1 citations
Computer Modeling in Engineering & Sciences
Machine Learning in Materials Science
0.52
article

Hybrid Taguchi and Machine Learning Framework for Optimizing and Predicting Mechanical Properties of Polyurethane/Nanodiamond Nanocomposites

Santosh Kumar Sahu, Markapudi Bhanu Prasad, Borhen Louhichi
article en
1 citations

Abstract

This study investigates the mechanical behavior of polyurethane (PU) nanocomposites reinforced with nanodiamonds (NDs) and proposes an integrated optimization–prediction framework that combines the Taguchi method with machi... | Find, read and cite all the research you need on Tech Science Press

Computer Modeling in Engineering & SciencesVol. 145(1)
Openalex Percentile: Top 31%
Machine Learning in Materials Science
0.52
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Hybrid Taguchi and Machine Learning Framework for Optimizing and Predicting Mechanical Properties of Polyurethane/Nanodiamond Nanocomposites — Santosh Kumar Sahu, Markapudi Bhanu Prasad, et al. · Computer Modeling in Engineering & Sciences (2025) | TGRS Research Map | TGRS