Please note: In order to keep Hive up to date and provide users with the best features, we are no longer able to fully support Internet Explorer. The site is still available to you, however some sections of the site may appear broken. We would encourage you to move to a more modern browser like Firefox, Edge or Chrome in order to experience the site fully.

Supporting your high street Find out how »
Artificial Intelligence-Aided Materials Design : AI-Algorithms and Case Studies on Alloys and Metallurgical Processes, Hardback Book

Artificial Intelligence-Aided Materials Design : AI-Algorithms and Case Studies on Alloys and Metallurgical Processes Hardback

Hardback

Only a few left - usually despatched within 24 hours

Description

This book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including hard and soft magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys.

Readers new to AI/ML algorithms can use this book as a starting point and use the MATLAB® and Python implementation of AI/ML algorithms through included case studies.

Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference. Offers advantages and limitations of several AI concepts and their proper implementation in various data types generated through experiments and computer simulations and from industries in different file formats Helps readers to develop predictive models through AI/ML algorithms by writing their own computer code or using resources where they do not have to write code Covers downloadable resources such as MATLAB GUI/APP and Python implementation that can be used on common mobile devices Discusses the CALPHAD approach and ways to use data generated from it Features a chapter on metallurgical/materials concepts to help readers understand the case studies and thus proper implementation of AI/ML algorithms under the framework of data-driven materials science Uses case studies to examine the importance of using unsupervised machine learning algorithms in determining patterns in datasetsThis book is written for materials scientists and metallurgists interested in the application of AI, ML, and data science in the development of new materials.

Information

Other Formats

£110.00

Only a few left - usually despatched within 24 hours
Add to Basket
Sign in to add to wishlist
 
Free Home Delivery

on all orders

 
Pick up orders

from local bookshops

Information