Prediction of thermal conductivity of polyvinylpyrrolidone (PVP) electrospun nanocomposite fibers using artificial neural network and prey-predator algorithm.
In this study, multilayer perception neural network (MLPNN) was employed to predict thermal conductivity of PVP electrospun nanocomposite fibers with multiwalled carbon nanotubes (MWCNTs) and Nickel Zinc ferrites [(Ni0.6Zn0.4) Fe2O4]. This is the second attempt on the application of MLPNN with prey...
Main Authors: | Waseem S Khan, Nawaf N Hamadneh, Waqar A Khan |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5608192?pdf=render |
Similar Items
-
Electrical and Thermal Characterization of Electrospun PVP Nanocomposite Fibers
by: Waseem S. Khan, et al.
Published: (2013-01-01) -
Fabrication and characterization of polyvinylpyrrolidone and polyacrylonitrile electrospun nanocomposite fibers
by: Khan, Waseem Sabir
Published: (2011) -
Optimization of Microchannel Heat Sinks Using Prey-Predator Algorithm and Artificial Neural Networks
by: Nawaf Hamadneh, et al.
Published: (2018-06-01) -
Towards Analysis and Optimization of Electrospun PVP (Polyvinylpyrrolidone) Nanofibers
by: Utkarsh, et al.
Published: (2020-01-01) -
Using Artificial Neural Network with Prey Predator Algorithm for Prediction of the COVID-19: The Case of Brazil and Mexico
by: Nawaf N. Hamadneh, et al.
Published: (2021-01-01)