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130626 ||| eng |
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|a 9783642288821
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|a Iordache, Octavian
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245 |
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|a Self-Evolvable Systems
|h Elektronische Ressource
|b Machine Learning in Social Media
|c by Octavian Iordache
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250 |
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|a 1st ed. 2012
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260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2012, 2012
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300 |
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|a XXII, 278 p
|b online resource
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505 |
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|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
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653 |
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|a Nonlinear Optics
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653 |
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|a Computational intelligence
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653 |
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|a Applied Dynamical Systems
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653 |
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|a Computational Intelligence
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653 |
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|a Nonlinear theories
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653 |
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|a Dynamics
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041 |
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7 |
|a eng
|2 ISO 639-2
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989 |
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|b Springer
|a Springer eBooks 2005-
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|a Understanding Complex Systems
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028 |
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|a 10.1007/978-3-642-28882-1
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|u https://doi.org/10.1007/978-3-642-28882-1?nosfx=y
|x Verlag
|3 Volltext
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|a 515.39
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520 |
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|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
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