Engineering cotton yarns with artificial neural networking (ANN) / Tasnim N. Shaikh, Sweety A. Agrawal

1. Classification of textile Yarns
1.1 Introduction
1.2 Types of textile fiber
1.3 Types of textile yarns
etc...

2. Attributes of cotton mixing
2.1 Need for mix formulation
2.2 Interrelationship between fiber characteristics and yarn quality
2.3 Contribution of fiber parameters on ring spun yarn quality & cost
etc...

3. Testing techniques used in yarn engineering
3.1 Introduction
3.2 Role of testing in cotton selection
3.3 Various fiber testing techniques
etc...

4. Statistical techniques used in yarn engineering
4.2 Analysis of test data
4.2.1 Measures of central tendencies
4.2.2 Measurement of dispersion
etc...

5. Artificial neural networking (ANN)
5.1 Introduction
5.2 Historical background for development of ANN
5.3 Basic concept of ANN (Artificial Neural Network)
etc...

6. Changes in mix formulation approach with the technological developments
6.1 Introduction
6.2 Basic objectives of mix formulation
6.3 Constraints for accurate mixing
etc...

7. Cotton fiber engineering
7.1 Introduction
7.2 Importance of cotton fiber engineering
7.3 Attributes of cotton fiber engineering
etc...

8. Yarn engineering by back propagation algorithm concept of ANN
8.1 Introduction
8.2 Reverse yarn engineering
8.2.1 Importance
8.2.2 Basic steps of networking
etc...

9. Optimization of yarn quality, cost and process parameters
9.1 Introduction
9.2 Components for optimization
9.3 Technological value of cotton mix
etc...

10. Case study
10.1 Introduction
10.2 Case study 1
10.2.1 Basic attributes used for ANN reverse yarn
etc...
Appendices

Includes bibliographic references