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Self-Evolvable Systems Machine Learning in Social Media /
This monograph presents key method to successfully manage the growing complexity of systems where conventional engineering and scientific methodologies and technologies based on learning and adaptability come to their limits and new ways are nowadays required. The transition from adaptable to evol...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2012.
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| Edición: | 1st ed. 2012. |
| Colección: | Understanding Complex Systems,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 024 | 7 | |a 10.1007/978-3-642-28882-1 |2 doi | |
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| 100 | 1 | |a Iordache, Octavian. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Self-Evolvable Systems |h [electronic resource] : |b Machine Learning in Social Media / |c by Octavian Iordache. |
| 250 | |a 1st ed. 2012. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2012. | |
| 300 | |a XXII, 278 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Understanding Complex Systems, |x 1860-0840 | |
| 505 | 0 | |a Introduction -- General Framework -- Differential Models -- Informational Criteria -- Self-Evolvability for Physical and Chemical Systems -- Self-Evolvability for Biosystems -- Self-Evolvability for Cognitive Systems -- Control Systems -- Manufacturing Systems -- Concept Lattices -- Design of Experiments -- Perspectives. | |
| 520 | |a This monograph presents key method to successfully manage the growing complexity of systems where conventional engineering and scientific methodologies and technologies based on learning and adaptability come to their limits and new ways are nowadays required. The transition from adaptable to evolvable and finally to self-evolvable systems is highlighted, self-properties such as self-organization, self-configuration, and self-repairing are introduced and challenges and limitations of the self-evolvable engineering systems are evaluated. | ||
| 650 | 0 | |a Dynamics. | |
| 650 | 0 | |a Nonlinear theories. | |
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Nonlinear Optics. | |
| 650 | 1 | 4 | |a Applied Dynamical Systems. |
| 650 | 2 | 4 | |a Computational Intelligence. |
| 650 | 2 | 4 | |a Nonlinear Optics. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783642288838 |
| 776 | 0 | 8 | |i Printed edition: |z 9783642431494 |
| 776 | 0 | 8 | |i Printed edition: |z 9783642288814 |
| 830 | 0 | |a Understanding Complex Systems, |x 1860-0840 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-642-28882-1 |z Texto Completo |
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