Tensile Properties Prediction of WFRP Composite Based on Machine Learning and ANN Models: An Experimental and Statistical Approach
- 28 April 2026
- journal article
- research article
- Published by Springer Nature in Journal of Materials Engineering and Performance
- Vol. 35 (30) , 1-14
Abstract
No abstract availableKeywords
This publication has 38 references indexed in Scilit:
- Advances in natural fiber polymer and PLA composites through artificial intelligence and machine learning integrationJournal of Polymer Research, 2025
- Mechanical Behavior Prediction of 3D‐Printed PLA/Wood Composites Using Artificial Neural Network and Fuzzy LogicPolymers for Advanced Technologies, 2025
- Applied Composite Materials Special Memorial Issue on Structural Integrity of Engineering Composite MaterialsApplied Composite Materials, 2024
- A review on recent applications of machine learning in mechanical properties of compositesPolymer Composites, 2024
- Response of Coconut Coir Filler-Reinforced Epoxy Composite Toward Cyclic Loading: Fatigue Property Evaluation2023
- Lignocellulosic fiber reinforced composites: Progress, performance, properties, applications, and future perspectivesPolymer Composites, 2021
- Quantitative probing of static and dynamic mechanical properties of different bio-filler-reinforced epoxy composite under assorted constraintsPolymer Bulletin, 2020
- Mechanical characterization and quantification of tensile, fracture and viscoelastic characteristics of wood filler reinforced epoxy compositeWood Science and Technology, 2018
- Optimisation of Mechanical Properties of Wood Dust-reinforced Epoxy Composite Using Grey Relational Analysis2014
- The Elements of Statistical Learning2009