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Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach

  • Sudipto Chaki
  • Sujit Ghosal

Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Also part of the SpringerBriefs in Computational Intelligence book sub series (BRIEFSINTELL)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Sudipto Chaki, Sujit Ghosal
    Pages 1-12

About this book

Introduction

This book presents the basics of the Laser Assisted Oxygen (LASOX) cutting process, its development, advantages and shortcomings, together with detailed information on the research work carried out to date regarding the modelling and optimization of the process. It introduces two integrated soft computing-based models consisting of Artificial Neural Networks (ANN-GA and ANN SA) for the modelling and optimization of LASOX cutting. It also includes an in-depth discussion on the basic working algorithms of soft computing tools such as Artificial Neural Networks, Genetic Algorithms, Simulated Annealing etc. The book not only provides an approach to optimizing LASOX by means of soft computing-based integrated models, but also illustrates the practical implementation of the proposed models.

Keywords

Artificial Neural Networks Genetic Algorithms Laser Cutting LASOX Simulated Annealing Soft Computing

Authors and affiliations

  • Sudipto Chaki
    • 1
  • Sujit Ghosal
    • 2
  1. 1.Department of Automobile EngineeringMCKV Institute of EngineeringHowrahIndia
  2. 2.Department of Mechanical EngineeringNetaji Subhas Engineering CollegeKolkataIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-04903-4
  • Copyright Information The Author(s), under exclusive license to Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Intelligent Technologies and Robotics
  • Print ISBN 978-3-030-04902-7
  • Online ISBN 978-3-030-04903-4
  • Series Print ISSN 2191-530X
  • Series Online ISSN 2191-5318
  • Buy this book on publisher's site