Advances in Computer Science for Engineering and Manufacturing
Seiten
2022
|
1st ed. 2022
Springer International Publishing (Verlag)
978-3-031-03876-1 (ISBN)
Springer International Publishing (Verlag)
978-3-031-03876-1 (ISBN)
The book's general scope covers the latest advances in the development of artificial intelligence systems and their applications in engineering and manufacturing. The book comprises refereed papers presented at the International Symposium on Engineering and Manufacturing (ISEM2021), held in Kyiv, Ukraine, on December 24-26, 2021.
Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular in engineering and manufacturing, to increase the effectiveness of the creation and diagnosis of appropriate technical solutions. In digital artificial intelligence systems, scientists endeavor to reproduce the innate intellectual abilities of humans and other organisms. In-depth studies of biological and self-organizing systems can provide new approaches to create more and more effective artificial intelligence methods. The topics of the included papers concern thematic materials in the following spheres: mathematics and computer algorithms; analysis of some technical solutions; technological. The book is a compilation of state-of-the-art papers in the field, covering a comprehensive range of subjects that are relevant to business managers and engineering professionals alike. The breadth and depth of these proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students interested in artificial intelligence systems and their growing applications. Specialists, students, and other groups of people who want to know how artificial intelligence systems can be used in the future will be the target audience for this book.
Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular in engineering and manufacturing, to increase the effectiveness of the creation and diagnosis of appropriate technical solutions. In digital artificial intelligence systems, scientists endeavor to reproduce the innate intellectual abilities of humans and other organisms. In-depth studies of biological and self-organizing systems can provide new approaches to create more and more effective artificial intelligence methods. The topics of the included papers concern thematic materials in the following spheres: mathematics and computer algorithms; analysis of some technical solutions; technological. The book is a compilation of state-of-the-art papers in the field, covering a comprehensive range of subjects that are relevant to business managers and engineering professionals alike. The breadth and depth of these proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students interested in artificial intelligence systems and their growing applications. Specialists, students, and other groups of people who want to know how artificial intelligence systems can be used in the future will be the target audience for this book.
| Erscheinungsdatum | 23.04.2022 |
|---|---|
| Reihe/Serie | Lecture Notes in Networks and Systems |
| Zusatzinfo | X, 388 p. 177 illus., 118 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 604 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Maschinenbau | |
| Schlagworte | Artificial Intelligence • Computational Intelligence • Computer Science • Engineering • ICAILE 2022 • ICAILE 2022 • information systems • ISEM 2021 • Manufacturing |
| ISBN-10 | 3-031-03876-2 / 3031038762 |
| ISBN-13 | 978-3-031-03876-1 / 9783031038761 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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