Modeling the sliding wear and friction properties of polyphenylene sulfide composites using artificial neural networks

Wear

Volumn 268, Issue 5-6, 2010, Pages 708-714

  Gyurova, Lada A ^a   Miniño Justel, Paz ^b   Schlarb, Alois K ^c  

^a INSTITUT FÜR VERBUNDWERKSTOFFE GMBH   (Germany)

^b UNIVERSITY OF VIGO   (Spain)

^c University of Koblenz Landau   (Germany)

Author keywords

Artificial neural network; Friction; Optimal brain surgeon algorithm; Polymer composites; Pruning; Wear

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COEFFICIENT OF FRICTIONS; COMPUTATIONAL COSTS; IMPORTANCE ANALYSIS; INPUT VARIABLES; NEW MATERIAL; OPTIMAL BRAIN SURGEON; OPTIMAL BRAIN SURGEON ALGORITHM; POLYMER COMPOSITE; POLYPHENYLENE SULFIDE COMPOSITES; POLYPHENYLENE SULFIDES; QUALITY OF PREDICTIONS; SLIDING WEAR; THERMO-MECHANICAL; TRIBOLOGICAL PROPERTIES; WEAR AND FRICTION; WEAR PROCESS; WEAR RATES;

COMPOSITE MATERIALS; FRICTION; OPTICAL BURST SWITCHING; OPTIMIZATION; SULFUR COMPOUNDS; TRIBOLOGY; WEAR OF MATERIALS;

NEURAL NETWORKS;

EID: 74649085479     PISSN: 00431648     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.wear.2009.11.008     Document Type: Article

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