Artificial neural networks applied to polymer composites: a review
By Zhongya Zhang, K. Friedrich. 2003
546 citations recorded by the source corpus.
Subfields: Mechanical Engineering, Mechanics of Materials, Polymers and Plastics
View Paper: https://www.semanticscholar.org/paper/82baccde37289b400296ec975906a0a5e4e1376a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Mechanical Engineering
- A. Lakshminarayanan
- V. Balasubramanian
- K. Friedrich
- M. Al-Haik
- Zhongya Zhang
- V.S. Senthil Kumar
- G. Elatharasan
- L. Chang
In Mechanics of Materials
- V. Balasubramanian
- A. Lakshminarayanan
- K. Friedrich
- Zhongya Zhang
- M. Yousuff Hussaini
- M. Al-Haik
- Hamid Garmestani
- L. Chang
In Polymers and Plastics
- V. Balasubramanian
- A. Lakshminarayanan
- K. Friedrich
- Zhongya Zhang
- M. Yousuff Hussaini
- M. Al-Haik
- Hamid Garmestani
- L. Chang
Citations in the corpus
- Comparison of RSM with ANN in predicting tensile strength of friction stir welded AA7039 aluminium alloy joints (2009, methodology): “Details on the neural network modeling approach are given elsewhere[22].”
- Prediction of nonlinear viscoelastic behavior of polymeric composites using an artificial neural network (2006, background): “As an alternative to traditional explicit constitutive modeling, several investigators recently suggested what might be called implicit constitutive modeling based on artificial neural networks (ANN) (see Zhang and Friedrich, 2003).”
- Prediction on wear properties of polymer composites with artificial neural networks (2007, background): “For this purpose, artificial neural network (ANN) has been introduced into this field in recent years [1].”