Hybrid Artificial Intelligence Models with Multi Objective Optimization for Prediction of Tribological Behavior of Polytetrafluoroethylene Matrix Composites

Hybrid Artificial Intelligence Models with Multi Objective Optimization for Prediction of Tribological Behavior of Polytetrafluoroethylene Matrix Composites

This study presents multi-response optimization and prediction tribological behaviors polytetrafluoroethylene (PTFE) matrix composites. For multi-response optimization, the Taguchi model was hybridized with grey relational analysis to produce grey relational grades (GRG). A support vector regression...

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Bibliographic Details
Main Authors: Musa Alhaji Ibrahim, Hüseyin Çamur, Mahmut A. Savaş, Alhassan Kawu Sabo, Mamunu Mustapha, Sani I. Abba
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Applied Sciences
Subjects:
PTFE
bronze
carbon
tribological behaviors
Taguchi
grey relational analysis
Online Access:https://www.mdpi.com/2076-3417/12/17/8671

Internet

https://www.mdpi.com/2076-3417/12/17/8671

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