Data-Driven Evolutionary Modeling in Materials Technology

ISBN-13: 9781032061733 / Angielski / Twarda / 2022 / 280 str.

Nirupam Chakraborti

Opis

This book presents the genetic and evolutionary, algorithms and strategies associated with pertinent issues in materials science domain. It discusses the procedures for evolutionary multi-objective optimization of objective functions including available professional and public domain codes and a gamut of recent applications.

Spis treści

1. Introduction
2. Data with random noise and its modeling
3. Nature inspired non-calculus optimization
4. Single-objective evolutionary algorithms
5. Multi-objective evolutionary optimization 
6. Evolutionary learning and optimization using Neural Net paradigm
7. Evolutionary learning and optimization using Genetic Programming paradigm 
8. The challenge of big data and Evolutionary Deep Learning
9. Software available in public domain and the commercial software
10. Applications in Iron and Steel making
11. Applications in chemical and metallurgical unit processing
12. Applications in Materials Design
13. Applications in Atomistic Materials Design
14. Applications in Manufacturing
15. Miscellaneous Applications