Porosity Characterization of Thermal Barrier Coatings by Ultrasound with Genetic Algorithm Backpropagation Neural Network

Porosity is considered as one of the most important indicators for the characterization of the comprehensive performance of thermal barrier coatings (TBCs). In this study, the ultrasonic technique and the artificial neural network optimized with the genetic algorithm (GA_BPNN) are combined to develo...

Full description

Saved in:

Bibliographic Details
Published in:	Complexity (New York, N.Y.) Vol. 2021; no. 1
Main Authors:	Zhang, Shuxiao, Lv, Gaolong, Guo, Shifeng, Zhang, Yanhui, Feng, Wei
Format:	Journal Article
Language:	English
Published:	Hoboken Hindawi 2021 John Wiley & Sons, Inc Wiley
Subjects:	Algorithms Analysis Artificial intelligence Artificial neural networks Back propagation Back propagation networks Coatings Genetic algorithms Machine learning Mathematical models Morphology Neural networks Nondestructive testing Numerical analysis Porosity Porous materials Predictions Principal components analysis Reflectance Simulation methods Support vector machines Thermal barrier coatings Thermodynamic properties Ultrasonic methods Velocity Wavelet transforms Zirconium dioxide China
ISSN:	1076-2787, 1099-0526
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!