Optimization of acrylic dry spinning production line by using artificial neural network and genetic algorithm

Journal of Applied Polymer Science

Volumn 120, Issue 2, 2011, Pages 735-744

  Vadood, M ^a   Semnani, D ^a   Morshed, M ^a  

^a ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

acrylic dry spinning; artificial neural network; genetic algorithm; optimization

Indexed keywords

ACID CONTENT; ACRYLIC FIBERS; ACTIVATION FUNCTIONS; ADAPTIVE LEARNING RATES; ARTIFICIAL NEURAL NETWORK; COLOR INDEX; COMPREHENSIVE STUDIES; COMPUTER ALGORITHM; DRY SPINNING; HIDDEN LAYERS; MUTATION RATES; NON-LINEAR RELATIONSHIPS; POPULATION SIZES; PRODUCTION LINE; PRODUCTION QUALITY; RETENTION TIME; SELECTION FUNCTION; SOLUTION VISCOSITY; TEST DATA; TRAINING ALGORITHMS; TRIAL-AND-ERROR METHOD;

CURING; FORECASTING; FORMIC ACID; GENETIC ALGORITHMS; LEARNING ALGORITHMS; MANUFACTURE; MESOPOROUS MATERIALS; OPTIMIZATION; POPULATION STATISTICS; SPINNING (FIBERS); SYNTHETIC FIBERS; WATER CONTENT;

NEURAL NETWORKS;

EID: 78650919386     PISSN: 00218995     EISSN: 10974628     Source Type: Journal    
DOI: 10.1002/app.33252     Document Type: Article

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