Composite Materials Technology
eBook - PDF

Composite Materials Technology

Neural Network Applications

  1. 368 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Composite Materials Technology

Neural Network Applications

About this book

Artificial neural networks (ANN) can provide new insight into the study of composite materials and can normally be combined with other artificial intelligence tools such as expert system, genetic algorithm, and fuzzy logic. Because research on this field is very new, there is only a limited amount of published literature on the subject.Compiling in

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Yes, you can access Composite Materials Technology by S.M. Sapuan, Iqbal Mohammed Mujtaba, S.M. Sapuan,Iqbal Mohammed Mujtaba in PDF and/or ePUB format, as well as other popular books in Mathematics & Mathematics General. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2009
Print ISBN
9780367384623
eBook ISBN
9781420093339
Edition
1
Topic
Mathematics
Subtopic
Mathematics General
Index
Mathematics

Table of contents

  1. Front cover
  2. Contents
  3. Preface
  4. Acknowledgments
  5. Editors
  6. Contributors
  7. Chapter 1. Application of Artificial Neural Network in Composites Materials
  8. Chapter 2. Neural Network Approaches for Defect Detection in Composite Materials
  9. Chapter 3. The Use of Artifical Neural Networks in Damage Detection and Assessment in Polymeric Composite Structures
  10. Chapter 4. Damage Identification and Localization of Carbon Fiber-Reinforced Plastic Composite Plate Using Outlier Analysis and Multiplayer Perception Neural Network
  11. Chapter 5. Damage Localization of Carbon Fiber-Reinforced Plastic Composite and Perspex Plates Using Novelty Indices and the Cross-Validation Set of Multilayer Perception Neural Network
  12. Chapter 6. Impact Damage Detection in a Composite Structure Using Artifical Neural Network
  13. Chapter 7. Artifical Neural Networks for Predicting the Mechanical Behavior of Cement-Based Composites after 100 Cycles of Aging
  14. Chapter 8. Fatigue Life Prediction of Fiber-Reinforced Composites Using Artifical Neural Networks
  15. Chapter 9. Optimizing Neural Network Prediction of Composite Fatigue Life Under Variable Amplitude Loading Using Bayesian Regularization
  16. Chapter 10. Free Vibration Analysis and Optimal Design of the Adhesively Bounded Composite Single Lap and Tubular Lap Joints
  17. Chapter 11. Determining Initial Design Parameters by Using Genetically Optimized Neural Network Systems
  18. Chapter 12. Development of a Prototype Computational Framework for Selection of Natural Fiber-Reinforced Polymer Composite Materials Using Neural Network
  19. Index
  20. Back cover