| Acknowledgement | 第5-6页 |
| Table of Contents | 第6-10页 |
| Abstract | 第10-16页 |
| List of Tables | 第17-19页 |
| List of Figures | 第19-21页 |
| CHAPTER ONE LITERATURE REVIEW | 第21-43页 |
| 1.1 Yarn Quality Prediction Models | 第21-36页 |
| 1.1.1 Mathematical and Empirical Models | 第21-28页 |
| 1.1.2 Statistical Models | 第28-31页 |
| 1.1.3 Artificial Neural Network Model | 第31-36页 |
| 1.2 Shortcomings of the Previous Research and outline of the present Research work | 第36-39页 |
| 1.3 Contributions of this Research work | 第39页 |
| 1.4 References | 第39-43页 |
| CHAPTER TWO PREDICTING YARN PROPERTIES USINGMULTI-LAYER PERCEPTRON(MLP) WITH LM ALGORITHM | 第43-76页 |
| 2.1 Brief Introduction of MLFN and MLP | 第43-51页 |
| 2.1.1 Neural Model | 第44-47页 |
| 2.1.1.1 Biological Neuron Model | 第44-45页 |
| 2.1.1.2 Artificial Neuron Model | 第45-47页 |
| 2.1.2 Network Architecture | 第47-49页 |
| 2.1.2.1 A Layer of Neurons | 第47-48页 |
| 2.1.2.2 Multiple Layers of Neurons | 第48-49页 |
| 2.1.3 MLFN and MLP | 第49-51页 |
| 2.2 The Design of MLP used for Predicting Yarn Properties | 第51-62页 |
| 2.2.1 Structure Design of MLP | 第51-52页 |
| 2.2.2 LM Training Algorithm for MLP | 第52-58页 |
| 2.2.3 Generalization Considerations | 第58-59页 |
| 2.2.4 Flowchart for Training MLP using LM algorithm | 第59-62页 |
| 2.3 Prediction of Yarn Quality Properties based on MLP network and LM Algorithms | 第62-73页 |
| 2.3.1 Input Factors and Data Pre-processing | 第62-66页 |
| 2.3.2 Prediction of Yarn Strength | 第66-68页 |
| 2.3.2.1 Training of the Yarn Strength Prediction Model | 第66-67页 |
| 2.3.2.2 Results and Discussions for Yarn Strength Prediction Model | 第67-68页 |
| 2.3.3 Prediction of Yarn Elongation | 第68-71页 |
| 2.3.3.1 Training of the Yarn Elongation Prediction Model | 第68-69页 |
| 2.3.3.2 Results and Discussions for Yarn Elongation Prediction Model | 第69-71页 |
| 2.3.4 Prediction of Yarn Unevenness | 第71-73页 |
| 2.3.4.1 Training of the Yarn Unevenness Prediction Model | 第71-72页 |
| 2.3.4.2 Results and Discussions for Yarn Unevenness Prediction Model | 第72-73页 |
| 2.4 Conclusions | 第73-74页 |
| 2.5 References | 第74-76页 |
| CHAPTER THREE IMPROVEMENT OF THE YARN QUALITY PREDICTION MLP MODELS USING PCA METHOD | 第76-95页 |
| 3.1 Basic Concept of PCA | 第76-80页 |
| 3.2 Improvement of Yarn Quality Properties Prediction MLP Models | 第80-86页 |
| 3.2.1 Improvement of Yarn Strength Model | 第80-82页 |
| 3.2.2 Improvement of Yarn Elongation Model | 第82-84页 |
| 3.2.3 Improvement of Yarn Unevenness Model | 第84-86页 |
| 3.3 Analysis of Factors affecting Yarn Quality Properties | 第86-92页 |
| 3.3.1 Analysis of Factors affecting Yarn Strength | 第87-89页 |
| 3.3.2 Analysis of Factors affecting Yarn Elongation | 第89-91页 |
| 3.3.3 Analysis of Factors affecting Yarn Unevenness | 第91-92页 |
| 3.4 Conclusions | 第92-93页 |
| 3.5 References | 第93-95页 |
| CHAPTER FOUR IMPROVEMENT OF YARN QUALITY PREDICTION MLP MODELS USING DELM HYBRID ALGORITHM | 第95-114页 |
| 4.1 Brief Introduction of DELM Hybrid Algorithm | 第95-98页 |
| 4.1.1 Differential Evolution(DE)Algorithm | 第96-98页 |
| 4.1.2 DELM Hybrid Training Algorithm | 第98页 |
| 4.2 Design of DELM Hybrid Algorithm used for Training MLP Model | 第98-102页 |
| 4.2.1 Input Data | 第98-99页 |
| 4.2.2 Flowchart for Training MLP using DELM algorithm | 第99-102页 |
| 4.3 Prediction of Yarn Quality Properties using DELM Hybrid Algorithm | 第102-112页 |
| 4.3.1 Prediction of Yarn Strength | 第103-106页 |
| 4.3.2 Prediction of Yarn Elongation | 第106-109页 |
| 4.3.3 Prediction of Yarn Unevenness | 第109-112页 |
| 4.4 Conclusion | 第112页 |
| 4.5 References | 第112-114页 |
| CHAPTER FIVE PERFROMANCE IMPROVEMENT OF YARN PROPERTIES PREDICTION MLP MODEL BY USING DE-ELMHYBRID ALGORITHM | 第114-138页 |
| 5.1 Introduction of Extreme Learning Machines(ELM) | 第114-120页 |
| 5.2 Design of Hybrid DE-ELM Algorithm | 第120-123页 |
| 5.3 Prediction of Yarn Quality Properties using ELM and DE-ELM Algorithms | 第123-136页 |
| 5.3.1 Prediction of Yarn Strength | 第124-128页 |
| 5.3.1.1 Prediction of Yarn Strength using ELM Algorithm | 第124-125页 |
| 5.3.1.2 Prediction of Yarn strength using DE-ELM Algorithm | 第125-127页 |
| 5.3.1.3 Comparison of LM,ELM,DELM and DE-ELM Strength Models | 第127-128页 |
| 5.3.2 Prediction of Yarn Elongation | 第128-132页 |
| 5.3.2.1 Prediction of Yarn Elongation using ELM algorithm | 第128-129页 |
| 5.3.2.2 Prediction of Yam Elongation using DE-ELM algorithm | 第129-131页 |
| 5.3.2.3 Comdarison of LM,ELM,DELM and DE-ELM Elongation Models | 第131-132页 |
| 5.3.3 Prediction of Yarn Unevenness | 第132-136页 |
| 5.3.3.1 Prediction of Yarn Unevenness using ELM algorithm | 第132-133页 |
| 5.3.3.2 Prediction of Yarn Unevenness using DE-ELM algorithm | 第133-136页 |
| 5.3.3.3 Comparison of LM,ELM,DELM and DE-ELM Unevenness models | 第136页 |
| 5.4 Conclusion | 第136-137页 |
| 5.5 References | 第137-138页 |
| CHAPTER SLX SUMMARY AND PROSPECTS FOR FUTURE WORK | 第138-143页 |
| 6.1 Summary | 第138-141页 |
| 6.2 Limitations of this Research Work and Prospects for Future Work | 第141-143页 |
| LIST OF PUBLICATIONS | 第143-144页 |
| APPENDIX | 第144-162页 |
