Modelling and optimisation of laser assisted oxygen (LASOX) cutting [electronic resource] : a soft computing based approach / by Sudipto Chaki, Sujit Ghosal.
- 作者： Chaki, Sudipto.
- 其他作者：
- 其他題名：
- SpringerBriefs in computational intelligence.
- 出版： Cham : Springer International Publishing : Imprint: Springer 2019.
- 叢書名： SpringerBriefs in computational intelligence,
- 主題： Oxyacetylene welding and cutting. , Laser beam cutting. , Computational Intelligence. , Manufacturing, Machines, Tools, Processes. , Artificial Intelligence.
- ISBN： 9783030049034 (electronic bk.) 、 9783030049027 (paper)
- URL：
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電子書(校內)
- 一般註：Preface -- Chapter 1. LASOX Cutting: Principles and Evolution -- Chapter 2. Integrated Soft Computing Based Methodologies for Modelling -- Chapter 3. Modelling and Optimisation of LASOX Cutting of Mild Steel: A Case Study. E1084學校採購電子書
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讀者標籤：
- 系統號： 000274387 | 機讀編目格式
館藏資訊
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.
摘要註
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.