| 書(shū)目名稱 | Modelling and Optimisation of Laser Assisted Oxygen (LASOX) Cutting: A Soft Computing Based Approach |
| 編輯 | Sudipto Chaki,Sujit Ghosal |
| 視頻video | http://file.papertrans.cn/637/636600/636600.mp4 |
| 概述 | Presents the basics, advantages and shortcomings of the LASOX cutting process, together with research on modelling and optimizing it.Introduces two integrated soft computing-based models consisting of |
| 叢書(shū)名稱 | SpringerBriefs in Applied Sciences and Technology |
| 圖書(shū)封面 |  |
| 描述 | 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. |
| 出版日期 | Book 2019 |
| 關(guān)鍵詞 | Artificial Neural Networks; Genetic Algorithms; Laser Cutting; LASOX; Simulated Annealing; Soft Computing |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-04903-4 |
| isbn_softcover | 978-3-030-04902-7 |
| isbn_ebook | 978-3-030-04903-4Series ISSN 2191-530X Series E-ISSN 2191-5318 |
| issn_series | 2191-530X |
| copyright | The Author(s), under exclusive license to Springer Nature Switzerland AG 2019 |
|Archiver|手機(jī)版|小黑屋|
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