Hybrid neural network‐based prediction model for tribological properties of polyamide6‐based friction materials

The hybrid neural network employed to predict the tribological properties of solid lubricants reinforced nano‐TiO2/polyamide6 composites was established based on the back propagation and radial basis function networks, and optimized by adaptive genetic algorithm. With such three factors as material...

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Veröffentlicht in:	Polymer composites 2017-08, Vol.38 (8), p.1705-1711
Hauptverfasser:	Li, Duxin, Lv, Ruoyun, Si, Gaojie, You, Yilan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive algorithms Back propagation networks Friction Genetic algorithms Loads (forces) Mathematical models Neural networks Polymers Prediction models Radial basis function Solid lubricants Titanium oxides Tribology Wear rate
Online-Zugang:	Volltext
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