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Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach / / by Sudipto Chaki, Sujit Ghosal



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Autore: Chaki Sudipto Visualizza persona
Titolo: Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach / / by Sudipto Chaki, Sujit Ghosal Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Edizione: 1st ed. 2019.
Descrizione fisica: 1 online resource (ix, 56 pages)
Disciplina: 671.5
671.53
Soggetto topico: Computational intelligence
Manufactures
Artificial intelligence
Computational Intelligence
Manufacturing, Machines, Tools, Processes
Artificial Intelligence
Persona (resp. second.): GhosalSujit
Nota di contenuto: 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.
Sommario/riassunto: 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.
Titolo autorizzato: Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach  Visualizza cluster
ISBN: 3-030-04903-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484618903321
Lo trovi qui: Univ. Federico II
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Serie: SpringerBriefs in Computational Intelligence, . 2625-3704