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Otimization of textile parameters and properties

 

This course focus on optimization, prediction, classification, clustering and identification of parameters, Properties and patterns of fibrous materials and textiles.

The major contents involves:

principles of neural networks of Heb, Delta, Perceptron, Kohonen, Associative, ART, Time-dependent, Recurrent and other neural networks with applications in textile science and technology. Genetic algorithm, swarm, annealing rules and C-mean clustering in optimization of textile parameters and properties and special applications in transformation equations of textile physics and chemistry. Fuzzy logic, fuzzy set theory and fuzzy systems and also fuzzy neural networks and application of these systems in textile parameters identification, control and optimization.

This course involves theoretical and experimental work especially software making, programming with Matlab software and data analysis of textile parameters for various kinds of fibrous materials and textile structures and textile processes.

Prerequisites: 

General Calulus

Differential Equations

Numerical Calculus

Linear Algebra

General Textile Technology Credits

General Textile Chemistry Credits

Grading Policy: 

Final 40%

Exercises/Softwares

  • Dfecect clasification by Perceptron: 10%
  • MRII: 10%
  • Textile patterns clustring by Kohonen or LVQ: 20%
  • Optimization of a textile process sample by GA and ANN: 20%
Teacher Assistants: 

Mr. Eng. Javad Yekrang    Email: javad.yekrang@tx.iut.ac.ir

 

Time: 

Sat. Thu. 8:00-9:30 AM       In Textile Engineering Department

Term: 
Winter 2013
Grade: 
Graduate

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