Prediction modeling of friction behavior of aluminum matrix composites using neural network and genetic algorithms under high velocity and dry sliding condition

Mocaxue Xuebao/Tribology

Volumn 25, Issue 6, 2005, Pages 545-549

  Qiu, Ming ^a,b   Zhang, Yong Zhen ^b   Zhu, Jun ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b HENAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Friction behavior; High velocity; Neural network; Reinforced aluminum

Indexed keywords

ALUMINUM; APPLICATIONS; BRAKING; DATABASE SYSTEMS; DRYING; DYNAMICS; FORECASTING; FRICTION; FUNCTIONS; GENETIC ALGORITHMS; NEURAL NETWORKS; PRESSURE; VELOCITY; WEAR OF MATERIALS;

DRY SLIDING; FRICTION BEHAVIOR; HIGH VELOCITY; REINFORCED ALUMINUM;

METALLIC MATRIX COMPOSITES;

EID: 31844437645     PISSN: 10040595     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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