Tribo-Informatics
eBook - ePub

Tribo-Informatics

The Systematic Fusion of AI and Tribology

  1. 230 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Tribo-Informatics

The Systematic Fusion of AI and Tribology

About this book

This book details how artificial intelligence and other informatic methods can be applied to the field of tribology. Using problems often found within tribological condition monitoring, behaviour prediction, system optimization and mechanism analysis, the book covers methods used such as Artificial Neural Networks (ANN).

Including case studies throughout, the book offers an accessible introduction to tribological research, beginning with background on the theory behind tribo-informatics, and updates in the latest technology. It describes how to establish a tribo-informatics database, methods through which to express tribo-systems such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF), and its applications. It can be used in state monitoring, behaviour prediction and system optimization. Through case studies, practical examples of how tribo-informatics can be implemented are shown throughout various industries.

This book will be of interest to students and researchers in the field of tribology, friction, wear and artificial intelligence.

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Yes, you can access Tribo-Informatics by Zhinan Zhang,Nian Yin in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Mechanical Engineering. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Preface
  7. Acknowledgments
  8. Author’s biography
  9. Chapter 1 Introduction
  10. Chapter 2 Conceptual Framework and Informational Expression of Tribo-Informatics
  11. Chapter 3 Methods and Implementation of Tribo-Informatics
  12. Chapter 4 Case Studies
  13. Chapter 5 Conclusion
  14. Index