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...

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Vydáno v:	Complexity (New York, N.Y.) Ročník 2021; číslo 1
Hlavní autoři:	Zhang, Shuxiao, Lv, Gaolong, Guo, Shifeng, Zhang, Yanhui, Feng, Wei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hoboken Hindawi 2021 John Wiley & Sons, Inc Wiley
Témata:	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
On-line přístup:	Získat plný text
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