Sustainable Materials
eBook - ePub

Sustainable Materials

The Role of Artificial Intelligence and Machine Learning

  1. 214 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Sustainable Materials

The Role of Artificial Intelligence and Machine Learning

About this book

The self-learning ability of machine learning algorithms makes the investigations more accurate and accommodates all the complex requirements. Development in neural codes can accommodate the data in all the forms such as numerical values as well as images. The techniques also review the sustainability, life-span, the energy consumption in production polymer, etc. This book addresses the design, characterization, and development of prediction analysis of sustainable polymer composites using machine learning algorithms.

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Yes, you can access Sustainable Materials by Akshansh Mishra,Vijaykumar S Jatti,Shivangi Paliwal in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Biology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Title Page
  3. Copyright Page
  4. Preface
  5. Contents
  6. Chapter 1 Artificial Intelligence in Material Science
  7. Chapter 2 Data Driven Artificial Intelligence Based Approach for the Determination of Structural Stress Distribution in ASTM D3039 Tensile Specimens of Carbon-Epoxy and Kevlar-Epoxy Based Composite Materials
  8. Chapter 3 Image Segmentation for Evaluating the Microstructure Features obtained from Magnesium Composites Processed through Squeeze Casting
  9. Chapter 4 Experimental Investigation of Bagasse Ash in Concrete Material
  10. Chapter 5 Computational Material Science for Cheminformatics Feature Descriptive Language (CFDL) with Categorical Data
  11. Chapter 6 Explicit Dynamic Crash Analysis of a Car Using a Metal, Composite Material and an Alloy
  12. Chapter 7 Optimizing Friction Stir Spot Welded ABS Weld Strength Using JAYA and Cohort Intelligence Algorithm
  13. Chapter 8 Supervised Machine Learning Based Classification of Dimensional Deviation of FDM 3D Printed Samples
  14. Chapter 9 Polymer Composite Flexural Strength Estimation using K-Nearest Neighbouring Classification Algorithm
  15. Chapter 10 Supervised Machine Learning Based Classification of Surface Roughness of Fused Deposition Modeling 3D Printed Samples
  16. Chapter 11 Polymer Composite Impact Strength Estimation using K-Nearest Neighbouring Classification Algorithm
  17. Index